EXISTENCE OF MILD SOLUTIONS FOR FRACTIONAL EVOLUTION EQUATIONS.

Size: px
Start display at page:

Download "EXISTENCE OF MILD SOLUTIONS FOR FRACTIONAL EVOLUTION EQUATIONS."

Transcription

1 Joural of Fractioal Calculus ad Applicatios, Vol. 2. Ja. 22, No., pp.. ISSN: EXISTENCE OF MILD SOLUTIONS FOR FRACTIONAL EVOLUTION EQUATIONS. ZUFENG ZHANG, BIN LIU Abstract. I this article, we establish sufficiet coditios for the existece of mild solutios for fractioal evolutio differetial equatios by usig a ew fixed poit theorem. The results obtaied here improve ad geeralize may kow results. A example is also give to illustrate our results.. Itroductio Our aim i this paper is to study the olocal iitial value problem { D q xt) = Axt) + ft, xt)), t [, ], x) = gx), where D q is the Caputo fractioal derivative of order < q <, A is the ifiitesimal geerator of a strogly cotiuous semigroup of bouded liear operator i.e. C -semigroup) T t) i Baach space X, f : [, ] X X ad g : C[, ]; X) X are appropriate fuctios to be specified later. Fractioal differetial equatios have appeared i may braches of physics, ecoomics ad techical scieces [, 2]. There has bee a cosiderable developmet i fractioal differetial equatios i the last decades. Recetly, May authors are iterested i the existece of mild solutios for fractioal evolutio equatios. I [3], El-Borai discussed the followig equatio i Baach X, { D α ut) = Aut) + Bt)ut), u) = u, where A geerates a aalytic semigroup ad the solutio was give i terms of some probability desities. I [4], Zhou ad Jiao cocered the existece ad uiqueess of mild solutios for fractioal evolutio equatios by some fixed poit theorems. Cao et al. [5] studied the α-mild solutios for a class of fractioal evolutio equatios ad optimal cotrols i fractioal powder space. For more 2 Mathematics Subject Classificatio. 26A33, 47J35. Key words ad phrases. Existece, Fractioal evolutio equatios, Mild solutio, Measure of ocompactess. Correspodig author. Submitted Oct. 9, 2. Published March, 22. Research supported by NNSF of Chia 722) ad Uiversity Sciece Foudatio of Ahui Provice KJ22A265) ad KJ22B87). )

2 2 ZUFENG ZHANG, BIN LIU JFCA-22/2 iformatio o this subjects, the readers may refer to [6]-[] ad the refereces therei. Very recetly, Zhu [] used the measure of ocompactess to discuss problem ) whe q =. Motivated by this paper we cotiue to study the existece of mild solutios for problem ) with a fixed poit theorem related to the measure of ocompactess which is firstly used to deal with fractioal evolutio equatios. We obtai the existece results without the compactess o T t) which are differet from may existig papers such as [4, 6, 7]. The rest of the paper will be orgaized as follows. I sectio 2 we will recall some basic defiitios ad lemmas from the measure of ocompactess, fractioal derivatio ad itegratio. Sectio 3 is devoted to the existece results for problem ). We shall preset i Sectio 4 a example which illustrates our mai theorems. 2. Prelimiaries I this sectio, we itroduce otatios, defiitios, ad prelimiary results which are used i the rest of the paper. Throughout this paper, we deote by R + ad N the set of positive real umbers ad the set of positive itegers. Let X, ) be a real Baach space. We deote by C[, ]; X) the space of X-valued cotiuous fuctios o [, ] with the x = sup{xt) : t [, ]}. Let L p [, ]; X) be the space of X-valued Bocher fuctio o [,] with the orm x L p = xs)p ds) p, p <. Defiitio 2. [2]). The Riema-Liouville fractioal itegral of order q R + of a fuctio f : R + X is defied by I q ft) = Γq) t s) q fs)ds, t >, provided the right-had side is poitwise defied o R +, where Γ is the gamma fuctio. Defiitio 2.2 [2]). The Caputo fractioal derivative of order < q < of a fuctio f : C R + ; X) is defied by D q ft) = Γ q) t s) q f s)ds, t >. Let α defie the Hausdorff measure of ocompactess o both X ad C[, ]; X). To prove our results we eed the followig lemmas. Lemma 2.3 [2]). If W C[, ]; X) is bouded, the αw t)) αw ) for every t [, ], where W t) = {xt); x W }. Furthermore if W is equicotiuous o [, ], the αw t)) is cotiuous o [, ] ad αw ) = sup{αw t)); t [, ]}. Lemma 2.4 [3]). If {u } = L [, ]; X) is uiformly itegrable, the α{u } =) is measurable ad { } ) α u s)ds 2 α{u s)} =)ds. = Lemma 2.5 [4]). If W is bouded, the for each ϵ >, there is a sequece {u } = W such that αw ) 2α{u } =) + ϵ.

3 JFCA-22/2 MILD SOLUTIONS FOR FRACTIONAL EVOLUTION EQUATIONS 3 Lemma 2.6 [5]). Suppose that x, the x e )x 2πx + 2x ) < Γx + ) < x e )x 2πx + 2x.5 ). Lemma 2.7 [6] Fixed Poit Theorem). Let G be a closed ad covex subset of a real Baach space X, let A : G G be a cotiuous operator ad AG) be bouded. For each bouded subset B G, set A B) = AB), A B) = AcoA B))), = 2, 3,..., if there exist a costat k < ad a positive iteger such that for each bouded subset B G, αa B)) kαb), the A has a fixed poit i G. 3. Mai results I this sectio we will establish the existece results by usig the Hausdorff measure of ocompactess. Based o referece [6], we give the defiitio of the mild solutios of problem ) as follows. Defiitio 3.. By the mild solutio of problem ), we mea that the fuctio x C[, ]; X) which satisfies where xt) = St)gx) + St) = Ψ q θ) = π Remark 3.2 [6]). t s) q Tt s)fs, xs))ds, t [, ], ξ q θ)t t q θ)dθ, Tt) = q ξ q θ) = q θ q Ψq θ q ), θξ q θ)t t q θ)dθ, 2) ) q Γq + ) θ siπq), θ R +.! = ξ q θ) is the probability desity fuctio defied o R + ad θξ q θ)dθ = θ q Ψ qθ)dθ = Γ + q). To state ad prove our mai results for the existece of mild solutios of problem ), we eed the followig hypotheses: H) The C -semigroup {T t)} t geerated by A is equicotiuous ad M = sup{t t); t [, )} < +. H2) The fuctio g : C[, ]; X) X is completely cotiuous, moreover there exist positive costats c ad d such that gx) cx + d, for every x C[, ]; X). H3) The fuctio f : [, ] X X satisfies the Carathéodory type coditios, i.e. ft, ) : X X is cotiuous for a.e. t [, ] ad f, x) : [, ] X is strogly measurable for each x C[, ], X). H4) There exist a fuctio m L p [, ]; R + ), < p < q ad a odecreasig cotiuous fuctio Ω : R + R + such that ft, x) mt)ωx) for all x X

4 4 ZUFENG ZHANG, BIN LIU JFCA-22/2 ad a.e. t [, ]. H5) There exists L L [, ]; R + ) such that for each bouded D X, αft, D)) Lt)αD), for a.e. t [, ]. Remark 3.3. i) If A geerates a aalytic semigroup or a differetiable semigroup {T t)} t, the {T t)} t is a equicotiuous see [8]). ii) If ft, x) ft, y) Lt)x y, Lt) L [, ]; R + ), x, y X, the we ca get αft, D)) Lt)αD) for each bouded D X ad a.e. t [, ] see []). For each positive costat r, let B r = {x C[, ], X); x r}, the B r is clearly a bouded closed ad covex subset i C[, ], X). Lemma 3.4. Assume that hypotheses H)-H4) hold, the i) For ay fixed t, St) ad Tt) defied i 2) are liear ad bouded operators, i.e. for ay x X, St)x Mx, Tt)x M Γq) x. ii) St) ad Tt) are strogly cotiuous. iii) The set {t t s)q Tt s)fs, xs))ds; x B r } is equicotiuous o [, ]. Proof. i) ad ii) were give i [6], we oly check iii) as follows. For x B r, t < t 2, we have = = 2 t 2 s) q Tt 2 s)fs, xs))ds t s) q Tt s)fs, xs))ds 2 q θt 2 s) q ξ q θ)t t 2 s) q θ)fs, xs))dθds q θt s) q ξ q θ)t t s) q θ)fs, xs))dθds 2 q θt 2 s) q ξ q θ)t t 2 s) q θ)fs, xs))dθds t + q θt 2 s) q ξ q θ)t t 2 s) q θ)fs, xs))dθds q θt s) q ξ q θ)t t 2 s) q θ)fs, xs))dθds + q θt s) q ξ q θ)t t 2 s) q θ)fs, xs))dθds q θt s) q ξ q θ)t t s) q θ)fs, xs))dθds 2 q θt 2 s) q ξ q θ)t t 2 s) q θ)fs, xs))dθds t + q θ[t 2 s) q t s) q ]ξ q θ)t t 2 s) q θ)fs, xs))dθds + q θt s) q ξ q θ)[t t 2 s) q θ) T t s) q θ)]fs, xs))dθds

5 JFCA-22/2 MILD SOLUTIONS FOR FRACTIONAL EVOLUTION EQUATIONS 5 = qi + I 2 + I 3 ), where I = I 2 = I 3 = 2 t From hypothesis H4), we have I MΩr) Γ + q) θt 2 s) q ξ q θ)t t 2 s) q θ)fs, xs))dθds, θ[t 2 s) q t s) q ]ξ q θ)t t 2 s) q θ)fs, xs))dθds, θt s) q ξ q θ)[t t 2 s) q θ) T t s) q θ)]fs, xs))dθds. 2 t t 2 s) q ms) ds MΩr) Γ + q) + η) p t 2 t ) +η) p) m L p, I 2 MΩr) Γ + q) MΩr)m L p Γ + q) t s) q t 2 s) q ) p ds ) p m L p ) p t s) η t 2 s) η )ds = MΩr)m L p t+η Γ + q) + η) p t +η 2 + t 2 t ) +η ) p MΩr)m L p Γ + q) + η) p t 2 t ) +η) p), where η = q p, ). Hece lim t 2 t I = ad lim t2 t I 2 =. O the other had, from H) ad the Lebesgue domiated covergece theorem, we get lim I 3 lim t 2 t t 2 t θt s) q ξ q θ)t t 2 s) q θ)fs, xs)) T t s) q θfs, xs))dθds =. θt s) q ξ q θ) lim t 2 t T t 2 s) q θ)fs, xs)) T t s) q θ)fs, xs))dθds Hece, 2 t 2 s) q Tt 2 s)fs, xs))ds t s) q Tt s)fs, xs))ds idepedetly of x B r as t 2 t. This completes the proof. Lemma 3.5. Suppose that < a <, b > are two fixed costats, let S = a +C a b a 2 b 2 ab b ) Γq + ) +C2 + +C Γ2q + ) Γ )q + ) +C. Γq + ) The, lim S =. Proof. Sice < a <, there exists a costat b > with a + b <.

6 6 ZUFENG ZHANG, BIN LIU JFCA-22/2 From < q <, we kow that there exists N such that, if > the q >. By Lemma 2.6 if >, the ) q ) q q q Γq + ) > 2πq >. e e Therefore, for >, we have Γq + ) < q e )q ). b O the other had, there exists 2 N such that < b for each > q 2. e )q Set 3 = max{, 2 }, for > 3, we divide S ito two parts where S = S + S, S = a + C a b Γq + ) + a 2 b 2 C2 Γ2q + ) + + a 3 b 3 C 3 Γ 3 q + ), S = C a 3+ 3 b 3+ Γ 3 + )q + ) + a C b 3+2 Γ 3 + 2)q + ) + + b C Γq + ). For > 3, we have = C a 3+ 3 b 3+ Γ 3 + )q + ) + a C b 3+2 Γ 3 + 2)q + ) + + b C Γq + ) C a 3+ 3 b 3+ a 3 2 b 3+2 b S 3+)q e ) q ) + 3+ C )q e ) q ) C C 3+ a 3 b 3+ + C 3+2 a 3 2 b Cb a + b). q e )q ) I view of a + b <, we have lim + S =. Sice lim + S = is obvious, we obtai lim + S =. The proof is completed. Theorem 3.6. If hypotheses H)-H5) are satisfied, the there is at least oe mild solutio for problem ) provided that there exists a costat r such that where η = q p Mcr + d) + MΩr) + η) p Γq) m L p is defied i the proof of Lemma 3.4. Proof. Defie operator F : C[; ], X) C[, ]; X) by F x)t) = St)gx) + r, 3) t s) q Tt s)fs, xs))ds, t [, ]. We ca easily show that F is cotiuous by the usual techiques see [4]). For ay x B r, we have F x)t) St)gx) + t s) q Tt s)fs, xs))ds = ξ q θ)t t q θ)gx)dθ + q t s) q θξ q θ)t t s) q θ)dθfs, xs))ds

7 JFCA-22/2 MILD SOLUTIONS FOR FRACTIONAL EVOLUTION EQUATIONS 7 Mcr + d) + MΩr) Γq) Mcr + d) + MΩr) Mcr + d) + t s) q ms)ds Γq) MΩr) + η) p Γq) m L p. t s) q p ds ) p m L p The from 3) we get F x r which meas that F : B r B r is a bouded operator. Let B = cof B r. By Lemma 2.5 ad the coditio gx) is compact, we get for ay B B ad ϵ >, there is a sequece {x } = B such that αf Bt)) = αf Bt)) ) 2α t s) q Tt s)fs, {x } =)ds +ϵ 4 t s) q αtt s)fs, {x } =))ds + ϵ 4M t s) q Ls)α{x } Γq) =)ds + ϵ 4M Γq) αb) t s) q Ls)ds + ϵ. From the fact that there is a cotiuous fuctio ϕ : [, ] R + such that for ay γ >, t s) q Ls) ϕs) ds < γ. We choose γ < Γq) 4M ad let M = max{ ϕt) : t [, ]}, the αf Bt)) 4M [ ] Γq) αb) t s) q Ls) ϕs) ds + t s) q ϕs) ds +ϵ 4M ) γ Γq) αb) + Mtq +ϵ. q From ϵ > is arbitrary, it follows that αf Bt)) a + b Γq + ) tq )αb), where a = 4Mγ Γq), b = 4MM. From Lemma 2.5, we kow for ay ϵ >, there exists a sequece {y } = cof B) such that αf 2 Bt)) = αf cof Bt))) ) 2α t s) q Tt s)fs, {y } =)ds +ϵ 4 t s) q αtt s)fs, {y } =))ds + ϵ 4M t s) q Ls)αF Bs))ds + ϵ Γq) 4M Γq) αb) [t s) q b Ls) ϕs) + ϕs) ]a + Γq + ) sq )ds + ϵ

8 8 ZUFENG ZHANG, BIN LIU JFCA-22/2 4M [a Γq) αb) + btq Γq + ) ) t s) q Ls) ϕs) ds t ] +M t s) q b a + Γq + ) sq )ds +ϵ a 2 bt q + 2a Γq + ) + b2 t 2q ) αb) + ϵ. Γ2q + ) From ϵ > is arbitrary, it follows that αf 2 Bt)) a 2 bt q + 2a Γq + ) + b2 t 2q ) αb). Γ2q + ) By the method of mathematical iductio, for ay positive iteger ad t [, ], we obtai αf Bt)) a + C a bt q Γq + ) + C2 a 2 b 2 t 2q Γ2q + ) + ) αb). +C a b t )q Γ )q + ) + C +C b t q Γq + ) Therefore, by Lemma 3.4 ad Lemma 2.3, we get αf B) a + Ca b Γq + ) + C2 a 2 b 2 Γ2q + ) + b b ) αb). a Γ )q + ) + C Γq + ) The from Lemma 3.4, there exists a positive iteger such that a + C a b Γq + ) + a 2 b 2 C2 Γ2q + ) + +C ab ) Γ )q + ) + b C = k <. Γ q + ) The αf B) kαb). From Lemma 2.7 we coclude that F has at least oe fixed poit i B, i.e. the olocal value problem ) has at least oe mild solutio i B. The proof is completed. Corollary 3.7. If the hypotheses H)-H5) are satisfied, the there is at least oe mild solutio for ) provided that Proof. m L p < lim if T + [T McT + d)] + η) p Γq). 4) MΩT ) 4) implies that there exists a costat r > such that Mcr + d) + MΩr) + η) p Γq) m L p r. The by Theorem 3.6 we kow the corollary is true. 4. A example Let X = L 2 R ). Cosider the followig fractioal parabolic olocal Cauchy problem. { D q ut, z) = Lu)t, z) + ft, ut, z)), t [, ], z R, u, z) = m i= Kz, y)ut R i, y)dy, z R, 5)

9 JFCA-22/2 MILD SOLUTIONS FOR FRACTIONAL EVOLUTION EQUATIONS 9 where D q is the Caputo fractioal partial derivative of order < q <, f is a give fuctio, m is a positive iteger, < t < t 2 < < t m <, Kz, y) L 2 R R ; R + ). Moreover, u Lu)t, z) = a ij z) t, z) + b i z) u t, z) + cz)ut, z), z i z j z i i,j= where give coefficiets a ij, b i, c, i, j =, 2,..., satisfy the usual uiformly ellipticity coditios. We defie a operator A by A = L with the domai i= DA) = {v ) X : H 2 R )}. From [9], we kow that A geerates a aalytic, ocompact semigroup {T t)} t o L 2 R ). I additio, there exists a costat M > such that M = sup{t t); t [, )} < +. The the system 5) ca be reformulated as follows i X, { D q xt) = Axt) + ft, xt)), t [, ], x) = gx), where xt) = ut, ), that is xt)z = ut, z), z R. The fuctio g : C[, ], X) X is give by m gx)z = K g xt i )z), i= where K g vz) = Kz, y)vy)dy for v X, z R. R Let s take q = 2, ft, xt)) = t 4 si xt). Firstly, we have H) ad H3) are satisfied. The from ft, xt)) t 4, we get H4) holds with Ωx) =. From ft, xt)) ft, yt)) t 4 x y ad Remark 3.3 we get that H5) is satisfied. Furthermore, ote that K g : X X is completely cotiuous ad assume that c = m K R R 2 z, y)dydz) 2, we get H2) is satisfied. If M c <, the there exists a costat r which satisfies 3). Accordig to Theorem 3.6, problem 5) has at least oe mild solutio provided that Mc <. Refereces [] K.B. Oldham, J. Spaier, The Fractioal Calculus, Academic Press, New York, Lodo, 974. [2] I. Podluby, Fractioal Differetial Equatio, Academic Press, Sa Diego, 999. [3] M.M. El-Borai, Some probability desities ad fudametal solutios of fractioal evolutio equatios, Chaos Solitos ad Fractals 4 22) [4] Y. Zhou, F. Jiao, Nolocal Cauchy problem for fractioal evolutio equatios, No. Aal. 2) [5] J. Cao, Q. Yag, Z. Huag, Optimal mild solutios ad weighted pseudo-almost periodic classical solutios of fractioal itegro-differetial equatios, No. Aal. 74 2) [6] J. Wag, Y. Zhou, A class of fractioal evolutio equatios ad optimal cotrols, No. Aal. 2 2) [7] X. Shu, Y. Lai, Y. Che, The existece of mild solutios for impulsive fractioal partial differetial equatios, No. Aal. 74 2) [8] C. Cuevas, C. Lizama, Almost automorphic solutios to a class of semiliear fractioal differetial equatios, Appl. Math. Lett. 2 28) [9] E. Herádez, D. O Rega, K. Balachadra, O recet developmets i the theory of abstract differetial equatios with fractioal derivatives, No. Aal. 73 2)

10 ZUFENG ZHANG, BIN LIU JFCA-22/2 [] C. Lizama, A operator theoretical approach to a class of fractioal order differetial equatios, Appl. Math. Lett. 24 2) [] T. Zhu, C. Sog, G. Li, Existece of mild solutios for abstract semiliear evolutio equatios i Baach spaces, No. Aal ) [2] J.Baas, K. Goebel, Measure of Nocompactess i Baach Spaces, i: Lecture Notes i Pure ad Applied Math, vol.6, Marcle Dekker, New York, 98. [3] H.Möch, Boudary value problems for oliear ordiary differetial equatios of secod order i Baach spaces, No. Aal. 4 98) [4] D. Bothe, Multivalued perturbatio of m-accretive differetial iclusios, Israel J. Math ) [5] F. Wag, Y. Zhao, A two-sided iequality of gamma fuctio, J. Math. Res. Expo ) [6] L. Liu, F. Guo, C. Wu, Y. Wu, Existece theorems of global solutios for oliear Volterra type itegral equatios i Baach spaces, J. Math. Aal. Appl ) [7] F. Maiardi, P. Paradisi, R. Goreflo, Probability distributios geerated by fractioal diffusio equatios, i: J. Kertesz, I. KodorEds), Ecoophysics: A Emergig Sciece, Kluwer, Dordrecht, 2. [8] A. Pazy, Semigroups of Liear Operators ad Applicatios to Partial Differetial Equatios, Spriger-Verlag, New York, 983. [9] B. Maslowski, D. Nualart, Evolutio equatios drive by a fractioal Browia motio, J. Fu. Aal ) Zufeg Zhag School of Mathematics ad Statistics, Huazhog Uiversity of Sciece ad Techology, Wuha, 4374, Chia address: jshyzzf@sohu.com Bi Liu School of Mathematics ad Statistics, Huazhog Uiversity of Sciece ad Techology, Wuha, 4374, Chia address: biliu@mail.hust.edu.c

SAMPLE QUESTIONS FOR FINAL EXAM. (1) (2) (3) (4) Find the following using the definition of the Riemann integral: (2x + 1)dx

SAMPLE QUESTIONS FOR FINAL EXAM. (1) (2) (3) (4) Find the following using the definition of the Riemann integral: (2x + 1)dx SAMPLE QUESTIONS FOR FINAL EXAM REAL ANALYSIS I FALL 006 3 4 Fid the followig usig the defiitio of the Riema itegral: a 0 x + dx 3 Cosider the partitio P x 0 3, x 3 +, x 3 +,......, x 3 3 + 3 of the iterval

More information

Our aim is to show that under reasonable assumptions a given 2π-periodic function f can be represented as convergent series

Our aim is to show that under reasonable assumptions a given 2π-periodic function f can be represented as convergent series 8 Fourier Series Our aim is to show that uder reasoable assumptios a give -periodic fuctio f ca be represeted as coverget series f(x) = a + (a cos x + b si x). (8.) By defiitio, the covergece of the series

More information

ON THE DENSE TRAJECTORY OF LASOTA EQUATION

ON THE DENSE TRAJECTORY OF LASOTA EQUATION UNIVERSITATIS IAGELLONICAE ACTA MATHEMATICA, FASCICULUS XLIII 2005 ON THE DENSE TRAJECTORY OF LASOTA EQUATION by Atoi Leo Dawidowicz ad Najemedi Haribash Abstract. I preseted paper the dese trajectory

More information

In nite Sequences. Dr. Philippe B. Laval Kennesaw State University. October 9, 2008

In nite Sequences. Dr. Philippe B. Laval Kennesaw State University. October 9, 2008 I ite Sequeces Dr. Philippe B. Laval Keesaw State Uiversity October 9, 2008 Abstract This had out is a itroductio to i ite sequeces. mai de itios ad presets some elemetary results. It gives the I ite Sequeces

More information

Section 11.3: The Integral Test

Section 11.3: The Integral Test Sectio.3: The Itegral Test Most of the series we have looked at have either diverged or have coverged ad we have bee able to fid what they coverge to. I geeral however, the problem is much more difficult

More information

Theorems About Power Series

Theorems About Power Series Physics 6A Witer 20 Theorems About Power Series Cosider a power series, f(x) = a x, () where the a are real coefficiets ad x is a real variable. There exists a real o-egative umber R, called the radius

More information

Asymptotic Growth of Functions

Asymptotic Growth of Functions CMPS Itroductio to Aalysis of Algorithms Fall 3 Asymptotic Growth of Fuctios We itroduce several types of asymptotic otatio which are used to compare the performace ad efficiecy of algorithms As we ll

More information

Properties of MLE: consistency, asymptotic normality. Fisher information.

Properties of MLE: consistency, asymptotic normality. Fisher information. Lecture 3 Properties of MLE: cosistecy, asymptotic ormality. Fisher iformatio. I this sectio we will try to uderstad why MLEs are good. Let us recall two facts from probability that we be used ofte throughout

More information

Lecture 13. Lecturer: Jonathan Kelner Scribe: Jonathan Pines (2009)

Lecture 13. Lecturer: Jonathan Kelner Scribe: Jonathan Pines (2009) 18.409 A Algorithmist s Toolkit October 27, 2009 Lecture 13 Lecturer: Joatha Keler Scribe: Joatha Pies (2009) 1 Outlie Last time, we proved the Bru-Mikowski iequality for boxes. Today we ll go over the

More information

ON AN INTEGRAL OPERATOR WHICH PRESERVE THE UNIVALENCE

ON AN INTEGRAL OPERATOR WHICH PRESERVE THE UNIVALENCE Proceedigs of the Iteratioal Coferece o Theory ad Applicatios of Mathematics ad Iformatics ICTAMI 3, Alba Iulia ON AN INTEGRAL OPERATOR WHICH PRESERVE THE UNIVALENCE by Maria E Gageoea ad Silvia Moldoveau

More information

A sharp Trudinger-Moser type inequality for unbounded domains in R n

A sharp Trudinger-Moser type inequality for unbounded domains in R n A sharp Trudiger-Moser type iequality for ubouded domais i R Yuxiag Li ad Berhard Ruf Abstract The Trudiger-Moser iequality states that for fuctios u H, 0 (Ω) (Ω R a bouded domai) with Ω u dx oe has Ω

More information

Convexity, Inequalities, and Norms

Convexity, Inequalities, and Norms Covexity, Iequalities, ad Norms Covex Fuctios You are probably familiar with the otio of cocavity of fuctios. Give a twicedifferetiable fuctio ϕ: R R, We say that ϕ is covex (or cocave up) if ϕ (x) 0 for

More information

Soving Recurrence Relations

Soving Recurrence Relations Sovig Recurrece Relatios Part 1. Homogeeous liear 2d degree relatios with costat coefficiets. Cosider the recurrece relatio ( ) T () + at ( 1) + bt ( 2) = 0 This is called a homogeeous liear 2d degree

More information

Annuities Under Random Rates of Interest II By Abraham Zaks. Technion I.I.T. Haifa ISRAEL and Haifa University Haifa ISRAEL.

Annuities Under Random Rates of Interest II By Abraham Zaks. Technion I.I.T. Haifa ISRAEL and Haifa University Haifa ISRAEL. Auities Uder Radom Rates of Iterest II By Abraham Zas Techio I.I.T. Haifa ISRAEL ad Haifa Uiversity Haifa ISRAEL Departmet of Mathematics, Techio - Israel Istitute of Techology, 3000, Haifa, Israel I memory

More information

1. MATHEMATICAL INDUCTION

1. MATHEMATICAL INDUCTION 1. MATHEMATICAL INDUCTION EXAMPLE 1: Prove that for ay iteger 1. Proof: 1 + 2 + 3 +... + ( + 1 2 (1.1 STEP 1: For 1 (1.1 is true, sice 1 1(1 + 1. 2 STEP 2: Suppose (1.1 is true for some k 1, that is 1

More information

Class Meeting # 16: The Fourier Transform on R n

Class Meeting # 16: The Fourier Transform on R n MATH 18.152 COUSE NOTES - CLASS MEETING # 16 18.152 Itroductio to PDEs, Fall 2011 Professor: Jared Speck Class Meetig # 16: The Fourier Trasform o 1. Itroductio to the Fourier Trasform Earlier i the course,

More information

A probabilistic proof of a binomial identity

A probabilistic proof of a binomial identity A probabilistic proof of a biomial idetity Joatho Peterso Abstract We give a elemetary probabilistic proof of a biomial idetity. The proof is obtaied by computig the probability of a certai evet i two

More information

THIN SEQUENCES AND THE GRAM MATRIX PAMELA GORKIN, JOHN E. MCCARTHY, SANDRA POTT, AND BRETT D. WICK

THIN SEQUENCES AND THE GRAM MATRIX PAMELA GORKIN, JOHN E. MCCARTHY, SANDRA POTT, AND BRETT D. WICK THIN SEQUENCES AND THE GRAM MATRIX PAMELA GORKIN, JOHN E MCCARTHY, SANDRA POTT, AND BRETT D WICK Abstract We provide a ew proof of Volberg s Theorem characterizig thi iterpolatig sequeces as those for

More information

Chapter 7 Methods of Finding Estimators

Chapter 7 Methods of Finding Estimators Chapter 7 for BST 695: Special Topics i Statistical Theory. Kui Zhag, 011 Chapter 7 Methods of Fidig Estimators Sectio 7.1 Itroductio Defiitio 7.1.1 A poit estimator is ay fuctio W( X) W( X1, X,, X ) of

More information

Infinite Sequences and Series

Infinite Sequences and Series CHAPTER 4 Ifiite Sequeces ad Series 4.1. Sequeces A sequece is a ifiite ordered list of umbers, for example the sequece of odd positive itegers: 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29...

More information

Modified Line Search Method for Global Optimization

Modified Line Search Method for Global Optimization Modified Lie Search Method for Global Optimizatio Cria Grosa ad Ajith Abraham Ceter of Excellece for Quatifiable Quality of Service Norwegia Uiversity of Sciece ad Techology Trodheim, Norway {cria, ajith}@q2s.tu.o

More information

A note on the boundary behavior for a modified Green function in the upper-half space

A note on the boundary behavior for a modified Green function in the upper-half space Zhag ad Pisarev Boudary Value Problems (015) 015:114 DOI 10.1186/s13661-015-0363-z RESEARCH Ope Access A ote o the boudary behavior for a modified Gree fuctio i the upper-half space Yulia Zhag1 ad Valery

More information

Sequences and Series

Sequences and Series CHAPTER 9 Sequeces ad Series 9.. Covergece: Defiitio ad Examples Sequeces The purpose of this chapter is to itroduce a particular way of geeratig algorithms for fidig the values of fuctios defied by their

More information

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES Read Sectio 1.5 (pages 5 9) Overview I Sectio 1.5 we lear to work with summatio otatio ad formulas. We will also itroduce a brief overview of sequeces,

More information

Vladimir N. Burkov, Dmitri A. Novikov MODELS AND METHODS OF MULTIPROJECTS MANAGEMENT

Vladimir N. Burkov, Dmitri A. Novikov MODELS AND METHODS OF MULTIPROJECTS MANAGEMENT Keywords: project maagemet, resource allocatio, etwork plaig Vladimir N Burkov, Dmitri A Novikov MODELS AND METHODS OF MULTIPROJECTS MANAGEMENT The paper deals with the problems of resource allocatio betwee

More information

Irreducible polynomials with consecutive zero coefficients

Irreducible polynomials with consecutive zero coefficients Irreducible polyomials with cosecutive zero coefficiets Theodoulos Garefalakis Departmet of Mathematics, Uiversity of Crete, 71409 Heraklio, Greece Abstract Let q be a prime power. We cosider the problem

More information

THE LEAST COMMON MULTIPLE OF A QUADRATIC SEQUENCE

THE LEAST COMMON MULTIPLE OF A QUADRATIC SEQUENCE THE LEAST COMMON MULTIPLE OF A QUADRATIC SEQUENCE JAVIER CILLERUELO Abstract. We obtai, for ay irreducible quadratic olyomial f(x = ax 2 + bx + c, the asymtotic estimate log l.c.m. {f(1,..., f(} log. Whe

More information

0.7 0.6 0.2 0 0 96 96.5 97 97.5 98 98.5 99 99.5 100 100.5 96.5 97 97.5 98 98.5 99 99.5 100 100.5

0.7 0.6 0.2 0 0 96 96.5 97 97.5 98 98.5 99 99.5 100 100.5 96.5 97 97.5 98 98.5 99 99.5 100 100.5 Sectio 13 Kolmogorov-Smirov test. Suppose that we have a i.i.d. sample X 1,..., X with some ukow distributio P ad we would like to test the hypothesis that P is equal to a particular distributio P 0, i.e.

More information

On Formula to Compute Primes. and the n th Prime

On Formula to Compute Primes. and the n th Prime Applied Mathematical cieces, Vol., 0, o., 35-35 O Formula to Compute Primes ad the th Prime Issam Kaddoura Lebaese Iteratioal Uiversity Faculty of Arts ad cieces, Lebao issam.kaddoura@liu.edu.lb amih Abdul-Nabi

More information

A Note on Sums of Greatest (Least) Prime Factors

A Note on Sums of Greatest (Least) Prime Factors It. J. Cotemp. Math. Scieces, Vol. 8, 203, o. 9, 423-432 HIKARI Ltd, www.m-hikari.com A Note o Sums of Greatest (Least Prime Factors Rafael Jakimczuk Divisio Matemática, Uiversidad Nacioal de Luá Bueos

More information

THE ABRACADABRA PROBLEM

THE ABRACADABRA PROBLEM THE ABRACADABRA PROBLEM FRANCESCO CARAVENNA Abstract. We preset a detailed solutio of Exercise E0.6 i [Wil9]: i a radom sequece of letters, draw idepedetly ad uiformly from the Eglish alphabet, the expected

More information

S. Tanny MAT 344 Spring 1999. be the minimum number of moves required.

S. Tanny MAT 344 Spring 1999. be the minimum number of moves required. S. Tay MAT 344 Sprig 999 Recurrece Relatios Tower of Haoi Let T be the miimum umber of moves required. T 0 = 0, T = 7 Iitial Coditios * T = T + $ T is a sequece (f. o itegers). Solve for T? * is a recurrece,

More information

Analysis Notes (only a draft, and the first one!)

Analysis Notes (only a draft, and the first one!) Aalysis Notes (oly a draft, ad the first oe!) Ali Nesi Mathematics Departmet Istabul Bilgi Uiversity Kuştepe Şişli Istabul Turkey aesi@bilgi.edu.tr Jue 22, 2004 2 Cotets 1 Prelimiaries 9 1.1 Biary Operatio...........................

More information

Department of Computer Science, University of Otago

Department of Computer Science, University of Otago Departmet of Computer Sciece, Uiversity of Otago Techical Report OUCS-2006-09 Permutatios Cotaiig May Patters Authors: M.H. Albert Departmet of Computer Sciece, Uiversity of Otago Micah Colema, Rya Fly

More information

Chapter 6: Variance, the law of large numbers and the Monte-Carlo method

Chapter 6: Variance, the law of large numbers and the Monte-Carlo method Chapter 6: Variace, the law of large umbers ad the Mote-Carlo method Expected value, variace, ad Chebyshev iequality. If X is a radom variable recall that the expected value of X, E[X] is the average value

More information

CS103A Handout 23 Winter 2002 February 22, 2002 Solving Recurrence Relations

CS103A Handout 23 Winter 2002 February 22, 2002 Solving Recurrence Relations CS3A Hadout 3 Witer 00 February, 00 Solvig Recurrece Relatios Itroductio A wide variety of recurrece problems occur i models. Some of these recurrece relatios ca be solved usig iteratio or some other ad

More information

PROCEEDINGS OF THE YEREVAN STATE UNIVERSITY AN ALTERNATIVE MODEL FOR BONUS-MALUS SYSTEM

PROCEEDINGS OF THE YEREVAN STATE UNIVERSITY AN ALTERNATIVE MODEL FOR BONUS-MALUS SYSTEM PROCEEDINGS OF THE YEREVAN STATE UNIVERSITY Physical ad Mathematical Scieces 2015, 1, p. 15 19 M a t h e m a t i c s AN ALTERNATIVE MODEL FOR BONUS-MALUS SYSTEM A. G. GULYAN Chair of Actuarial Mathematics

More information

1 Computing the Standard Deviation of Sample Means

1 Computing the Standard Deviation of Sample Means Computig the Stadard Deviatio of Sample Meas Quality cotrol charts are based o sample meas ot o idividual values withi a sample. A sample is a group of items, which are cosidered all together for our aalysis.

More information

AP Calculus AB 2006 Scoring Guidelines Form B

AP Calculus AB 2006 Scoring Guidelines Form B AP Calculus AB 6 Scorig Guidelies Form B The College Board: Coectig Studets to College Success The College Board is a ot-for-profit membership associatio whose missio is to coect studets to college success

More information

THE HEIGHT OF q-binary SEARCH TREES

THE HEIGHT OF q-binary SEARCH TREES THE HEIGHT OF q-binary SEARCH TREES MICHAEL DRMOTA AND HELMUT PRODINGER Abstract. q biary search trees are obtaied from words, equipped with the geometric distributio istead of permutatios. The average

More information

Overview of some probability distributions.

Overview of some probability distributions. Lecture Overview of some probability distributios. I this lecture we will review several commo distributios that will be used ofte throughtout the class. Each distributio is usually described by its probability

More information

Entropy of bi-capacities

Entropy of bi-capacities Etropy of bi-capacities Iva Kojadiovic LINA CNRS FRE 2729 Site école polytechique de l uiv. de Nates Rue Christia Pauc 44306 Nates, Frace iva.kojadiovic@uiv-ates.fr Jea-Luc Marichal Applied Mathematics

More information

Lecture 3. denote the orthogonal complement of S k. Then. 1 x S k. n. 2 x T Ax = ( ) λ x. with x = 1, we have. i = λ k x 2 = λ k.

Lecture 3. denote the orthogonal complement of S k. Then. 1 x S k. n. 2 x T Ax = ( ) λ x. with x = 1, we have. i = λ k x 2 = λ k. 18.409 A Algorithmist s Toolkit September 17, 009 Lecture 3 Lecturer: Joatha Keler Scribe: Adre Wibisoo 1 Outlie Today s lecture covers three mai parts: Courat-Fischer formula ad Rayleigh quotiets The

More information

Incremental calculation of weighted mean and variance

Incremental calculation of weighted mean and variance Icremetal calculatio of weighted mea ad variace Toy Fich faf@cam.ac.uk dot@dotat.at Uiversity of Cambridge Computig Service February 009 Abstract I these otes I eplai how to derive formulae for umerically

More information

Lecture 5: Span, linear independence, bases, and dimension

Lecture 5: Span, linear independence, bases, and dimension Lecture 5: Spa, liear idepedece, bases, ad dimesio Travis Schedler Thurs, Sep 23, 2010 (versio: 9/21 9:55 PM) 1 Motivatio Motivatio To uderstad what it meas that R has dimesio oe, R 2 dimesio 2, etc.;

More information

On the L p -conjecture for locally compact groups

On the L p -conjecture for locally compact groups Arch. Math. 89 (2007), 237 242 c 2007 Birkhäuser Verlag Basel/Switzerlad 0003/889X/030237-6, ublished olie 2007-08-0 DOI 0.007/s0003-007-993-x Archiv der Mathematik O the L -cojecture for locally comact

More information

Maximum Likelihood Estimators.

Maximum Likelihood Estimators. Lecture 2 Maximum Likelihood Estimators. Matlab example. As a motivatio, let us look at oe Matlab example. Let us geerate a radom sample of size 00 from beta distributio Beta(5, 2). We will lear the defiitio

More information

Degree of Approximation of Continuous Functions by (E, q) (C, δ) Means

Degree of Approximation of Continuous Functions by (E, q) (C, δ) Means Ge. Math. Notes, Vol. 11, No. 2, August 2012, pp. 12-19 ISSN 2219-7184; Copyright ICSRS Publicatio, 2012 www.i-csrs.org Available free olie at http://www.gema.i Degree of Approximatio of Cotiuous Fuctios

More information

WHEN IS THE (CO)SINE OF A RATIONAL ANGLE EQUAL TO A RATIONAL NUMBER?

WHEN IS THE (CO)SINE OF A RATIONAL ANGLE EQUAL TO A RATIONAL NUMBER? WHEN IS THE (CO)SINE OF A RATIONAL ANGLE EQUAL TO A RATIONAL NUMBER? JÖRG JAHNEL 1. My Motivatio Some Sort of a Itroductio Last term I tought Topological Groups at the Göttige Georg August Uiversity. This

More information

An Efficient Polynomial Approximation of the Normal Distribution Function & Its Inverse Function

An Efficient Polynomial Approximation of the Normal Distribution Function & Its Inverse Function A Efficiet Polyomial Approximatio of the Normal Distributio Fuctio & Its Iverse Fuctio Wisto A. Richards, 1 Robi Atoie, * 1 Asho Sahai, ad 3 M. Raghuadh Acharya 1 Departmet of Mathematics & Computer Sciece;

More information

FIBONACCI NUMBERS: AN APPLICATION OF LINEAR ALGEBRA. 1. Powers of a matrix

FIBONACCI NUMBERS: AN APPLICATION OF LINEAR ALGEBRA. 1. Powers of a matrix FIBONACCI NUMBERS: AN APPLICATION OF LINEAR ALGEBRA. Powers of a matrix We begi with a propositio which illustrates the usefuless of the diagoalizatio. Recall that a square matrix A is diogaalizable if

More information

3. Greatest Common Divisor - Least Common Multiple

3. Greatest Common Divisor - Least Common Multiple 3 Greatest Commo Divisor - Least Commo Multiple Defiitio 31: The greatest commo divisor of two atural umbers a ad b is the largest atural umber c which divides both a ad b We deote the greatest commo gcd

More information

A Combined Continuous/Binary Genetic Algorithm for Microstrip Antenna Design

A Combined Continuous/Binary Genetic Algorithm for Microstrip Antenna Design A Combied Cotiuous/Biary Geetic Algorithm for Microstrip Atea Desig Rady L. Haupt The Pesylvaia State Uiversity Applied Research Laboratory P. O. Box 30 State College, PA 16804-0030 haupt@ieee.org Abstract:

More information

I. Chi-squared Distributions

I. Chi-squared Distributions 1 M 358K Supplemet to Chapter 23: CHI-SQUARED DISTRIBUTIONS, T-DISTRIBUTIONS, AND DEGREES OF FREEDOM To uderstad t-distributios, we first eed to look at aother family of distributios, the chi-squared distributios.

More information

A RANDOM PERMUTATION MODEL ARISING IN CHEMISTRY

A RANDOM PERMUTATION MODEL ARISING IN CHEMISTRY J. Appl. Prob. 45, 060 070 2008 Prited i Eglad Applied Probability Trust 2008 A RANDOM PERMUTATION MODEL ARISING IN CHEMISTRY MARK BROWN, The City College of New York EROL A. PEKÖZ, Bosto Uiversity SHELDON

More information

The analysis of the Cournot oligopoly model considering the subjective motive in the strategy selection

The analysis of the Cournot oligopoly model considering the subjective motive in the strategy selection The aalysis of the Courot oligopoly model cosiderig the subjective motive i the strategy selectio Shigehito Furuyama Teruhisa Nakai Departmet of Systems Maagemet Egieerig Faculty of Egieerig Kasai Uiversity

More information

INFINITE SERIES KEITH CONRAD

INFINITE SERIES KEITH CONRAD INFINITE SERIES KEITH CONRAD. Itroductio The two basic cocepts of calculus, differetiatio ad itegratio, are defied i terms of limits (Newto quotiets ad Riema sums). I additio to these is a third fudametal

More information

MARTINGALES AND A BASIC APPLICATION

MARTINGALES AND A BASIC APPLICATION MARTINGALES AND A BASIC APPLICATION TURNER SMITH Abstract. This paper will develop the measure-theoretic approach to probability i order to preset the defiitio of martigales. From there we will apply this

More information

Chapter 5: Inner Product Spaces

Chapter 5: Inner Product Spaces Chapter 5: Ier Product Spaces Chapter 5: Ier Product Spaces SECION A Itroductio to Ier Product Spaces By the ed of this sectio you will be able to uderstad what is meat by a ier product space give examples

More information

Partial Di erential Equations

Partial Di erential Equations Partial Di eretial Equatios Partial Di eretial Equatios Much of moder sciece, egieerig, ad mathematics is based o the study of partial di eretial equatios, where a partial di eretial equatio is a equatio

More information

Lecture 4: Cheeger s Inequality

Lecture 4: Cheeger s Inequality Spectral Graph Theory ad Applicatios WS 0/0 Lecture 4: Cheeger s Iequality Lecturer: Thomas Sauerwald & He Su Statemet of Cheeger s Iequality I this lecture we assume for simplicity that G is a d-regular

More information

Factors of sums of powers of binomial coefficients

Factors of sums of powers of binomial coefficients ACTA ARITHMETICA LXXXVI.1 (1998) Factors of sums of powers of biomial coefficiets by Neil J. Cali (Clemso, S.C.) Dedicated to the memory of Paul Erdős 1. Itroductio. It is well ow that if ( ) a f,a = the

More information

A Faster Clause-Shortening Algorithm for SAT with No Restriction on Clause Length

A Faster Clause-Shortening Algorithm for SAT with No Restriction on Clause Length Joural o Satisfiability, Boolea Modelig ad Computatio 1 2005) 49-60 A Faster Clause-Shorteig Algorithm for SAT with No Restrictio o Clause Legth Evgey Datsi Alexader Wolpert Departmet of Computer Sciece

More information

CS103X: Discrete Structures Homework 4 Solutions

CS103X: Discrete Structures Homework 4 Solutions CS103X: Discrete Structures Homewor 4 Solutios Due February 22, 2008 Exercise 1 10 poits. Silico Valley questios: a How may possible six-figure salaries i whole dollar amouts are there that cotai at least

More information

3 Basic Definitions of Probability Theory

3 Basic Definitions of Probability Theory 3 Basic Defiitios of Probability Theory 3defprob.tex: Feb 10, 2003 Classical probability Frequecy probability axiomatic probability Historical developemet: Classical Frequecy Axiomatic The Axiomatic defiitio

More information

LECTURE 13: Cross-validation

LECTURE 13: Cross-validation LECTURE 3: Cross-validatio Resampli methods Cross Validatio Bootstrap Bias ad variace estimatio with the Bootstrap Three-way data partitioi Itroductio to Patter Aalysis Ricardo Gutierrez-Osua Texas A&M

More information

Data Analysis and Statistical Behaviors of Stock Market Fluctuations

Data Analysis and Statistical Behaviors of Stock Market Fluctuations 44 JOURNAL OF COMPUTERS, VOL. 3, NO. 0, OCTOBER 2008 Data Aalysis ad Statistical Behaviors of Stock Market Fluctuatios Ju Wag Departmet of Mathematics, Beijig Jiaotog Uiversity, Beijig 00044, Chia Email:

More information

Confidence Intervals for One Mean

Confidence Intervals for One Mean Chapter 420 Cofidece Itervals for Oe Mea Itroductio This routie calculates the sample size ecessary to achieve a specified distace from the mea to the cofidece limit(s) at a stated cofidece level for a

More information

The Gompertz Makeham coupling as a Dynamic Life Table. Abraham Zaks. Technion I.I.T. Haifa ISRAEL. Abstract

The Gompertz Makeham coupling as a Dynamic Life Table. Abraham Zaks. Technion I.I.T. Haifa ISRAEL. Abstract The Gompertz Makeham couplig as a Dyamic Life Table By Abraham Zaks Techio I.I.T. Haifa ISRAEL Departmet of Mathematics, Techio - Israel Istitute of Techology, 32000, Haifa, Israel Abstract A very famous

More information

Research Article Sign Data Derivative Recovery

Research Article Sign Data Derivative Recovery Iteratioal Scholarly Research Network ISRN Applied Mathematics Volume 0, Article ID 63070, 7 pages doi:0.540/0/63070 Research Article Sig Data Derivative Recovery L. M. Housto, G. A. Glass, ad A. D. Dymikov

More information

A Recursive Formula for Moments of a Binomial Distribution

A Recursive Formula for Moments of a Binomial Distribution A Recursive Formula for Momets of a Biomial Distributio Árpád Béyi beyi@mathumassedu, Uiversity of Massachusetts, Amherst, MA 01003 ad Saverio M Maago smmaago@psavymil Naval Postgraduate School, Moterey,

More information

NOTES ON PROBABILITY Greg Lawler Last Updated: March 21, 2016

NOTES ON PROBABILITY Greg Lawler Last Updated: March 21, 2016 NOTES ON PROBBILITY Greg Lawler Last Updated: March 21, 2016 Overview This is a itroductio to the mathematical foudatios of probability theory. It is iteded as a supplemet or follow-up to a graduate course

More information

Building Blocks Problem Related to Harmonic Series

Building Blocks Problem Related to Harmonic Series TMME, vol3, o, p.76 Buildig Blocks Problem Related to Harmoic Series Yutaka Nishiyama Osaka Uiversity of Ecoomics, Japa Abstract: I this discussio I give a eplaatio of the divergece ad covergece of ifiite

More information

Chapter 7 - Sampling Distributions. 1 Introduction. What is statistics? It consist of three major areas:

Chapter 7 - Sampling Distributions. 1 Introduction. What is statistics? It consist of three major areas: Chapter 7 - Samplig Distributios 1 Itroductio What is statistics? It cosist of three major areas: Data Collectio: samplig plas ad experimetal desigs Descriptive Statistics: umerical ad graphical summaries

More information

AMS 2000 subject classification. Primary 62G08, 62G20; secondary 62G99

AMS 2000 subject classification. Primary 62G08, 62G20; secondary 62G99 VARIABLE SELECTION IN NONPARAMETRIC ADDITIVE MODELS Jia Huag 1, Joel L. Horowitz 2 ad Fegrog Wei 3 1 Uiversity of Iowa, 2 Northwester Uiversity ad 3 Uiversity of West Georgia Abstract We cosider a oparametric

More information

Rényi Divergence and L p -affine surface area for convex bodies

Rényi Divergence and L p -affine surface area for convex bodies Réyi Divergece ad L p -affie surface area for covex bodies Elisabeth M. Werer Abstract We show that the fudametal objects of the L p -Bru-Mikowski theory, amely the L p -affie surface areas for a covex

More information

Study on the application of the software phase-locked loop in tracking and filtering of pulse signal

Study on the application of the software phase-locked loop in tracking and filtering of pulse signal Advaced Sciece ad Techology Letters, pp.31-35 http://dx.doi.org/10.14257/astl.2014.78.06 Study o the applicatio of the software phase-locked loop i trackig ad filterig of pulse sigal Sog Wei Xia 1 (College

More information

Institute of Actuaries of India Subject CT1 Financial Mathematics

Institute of Actuaries of India Subject CT1 Financial Mathematics Istitute of Actuaries of Idia Subject CT1 Fiacial Mathematics For 2014 Examiatios Subject CT1 Fiacial Mathematics Core Techical Aim The aim of the Fiacial Mathematics subject is to provide a groudig i

More information

Elementary Theory of Russian Roulette

Elementary Theory of Russian Roulette Elemetary Theory of Russia Roulette -iterestig patters of fractios- Satoshi Hashiba Daisuke Miematsu Ryohei Miyadera Itroductio. Today we are goig to study mathematical theory of Russia roulette. If some

More information

Trigonometric Form of a Complex Number. The Complex Plane. axis. ( 2, 1) or 2 i FIGURE 6.44. The absolute value of the complex number z a bi is

Trigonometric Form of a Complex Number. The Complex Plane. axis. ( 2, 1) or 2 i FIGURE 6.44. The absolute value of the complex number z a bi is 0_0605.qxd /5/05 0:45 AM Page 470 470 Chapter 6 Additioal Topics i Trigoometry 6.5 Trigoometric Form of a Complex Number What you should lear Plot complex umbers i the complex plae ad fid absolute values

More information

Metric, Normed, and Topological Spaces

Metric, Normed, and Topological Spaces Chapter 13 Metric, Normed, ad Topological Spaces A metric space is a set X that has a otio of the distace d(x, y) betwee every pair of poits x, y X. A fudametal example is R with the absolute-value metric

More information

Overview on S-Box Design Principles

Overview on S-Box Design Principles Overview o S-Box Desig Priciples Debdeep Mukhopadhyay Assistat Professor Departmet of Computer Sciece ad Egieerig Idia Istitute of Techology Kharagpur INDIA -721302 What is a S-Box? S-Boxes are Boolea

More information

UC Berkeley Department of Electrical Engineering and Computer Science. EE 126: Probablity and Random Processes. Solutions 9 Spring 2006

UC Berkeley Department of Electrical Engineering and Computer Science. EE 126: Probablity and Random Processes. Solutions 9 Spring 2006 Exam format UC Bereley Departmet of Electrical Egieerig ad Computer Sciece EE 6: Probablity ad Radom Processes Solutios 9 Sprig 006 The secod midterm will be held o Wedesday May 7; CHECK the fial exam

More information

D I S C U S S I O N P A P E R

D I S C U S S I O N P A P E R I N S T I T U T D E S T A T I S T I Q U E B I O S T A T I S T I Q U E E T S C I E N C E S A C T U A R I E L L E S ( I S B A UNIVERSITÉ CATHOLIQUE DE LOUVAIN D I S C U S S I O N P A P E R 2012/27 Worst-case

More information

Ekkehart Schlicht: Economic Surplus and Derived Demand

Ekkehart Schlicht: Economic Surplus and Derived Demand Ekkehart Schlicht: Ecoomic Surplus ad Derived Demad Muich Discussio Paper No. 2006-17 Departmet of Ecoomics Uiversity of Muich Volkswirtschaftliche Fakultät Ludwig-Maximilias-Uiversität Müche Olie at http://epub.ub.ui-mueche.de/940/

More information

The Stable Marriage Problem

The Stable Marriage Problem The Stable Marriage Problem William Hut Lae Departmet of Computer Sciece ad Electrical Egieerig, West Virgiia Uiversity, Morgatow, WV William.Hut@mail.wvu.edu 1 Itroductio Imagie you are a matchmaker,

More information

Acta Acad. Paed. Agriensis, Sectio Mathematicae 29 (2002) 77 87. ALMOST SURE FUNCTIONAL LIMIT THEOREMS IN L p( ]0, 1[ ), WHERE 1 p <

Acta Acad. Paed. Agriensis, Sectio Mathematicae 29 (2002) 77 87. ALMOST SURE FUNCTIONAL LIMIT THEOREMS IN L p( ]0, 1[ ), WHERE 1 p < Acta Acad. Paed. Agriesis, Sectio Mathematicae 29 22) 77 87 ALMOST SUR FUNCTIONAL LIMIT THORMS IN L ], [ ), WHR < József Túri Nyíregyháza, Hugary) Dedicated to the memory of Professor Péter Kiss Abstract.

More information

.04. This means $1000 is multiplied by 1.02 five times, once for each of the remaining sixmonth

.04. This means $1000 is multiplied by 1.02 five times, once for each of the remaining sixmonth Questio 1: What is a ordiary auity? Let s look at a ordiary auity that is certai ad simple. By this, we mea a auity over a fixed term whose paymet period matches the iterest coversio period. Additioally,

More information

Some Inequalities for p-geominimal Surface Area and Related Results

Some Inequalities for p-geominimal Surface Area and Related Results IAENG Iteratioal Joural of Applied Mathematics, 46:1, IJAM_46_1_14 Some Iequalities for p-geomiimal Surface Area ad Related Results Togyi Ma, Yibi Feg Abstract The cocepts of p-affie ad p-geomiimal surface

More information

Application and research of fuzzy clustering analysis algorithm under micro-lecture English teaching mode

Application and research of fuzzy clustering analysis algorithm under micro-lecture English teaching mode SHS Web of Cofereces 25, shscof/20162501018 Applicatio ad research of fuzzy clusterig aalysis algorithm uder micro-lecture Eglish teachig mode Yig Shi, Wei Dog, Chuyi Lou & Ya Dig Qihuagdao Istitute of

More information

Heavy Traffic Analysis of a Simple Closed Loop Supply Chain

Heavy Traffic Analysis of a Simple Closed Loop Supply Chain Heavy Traffic Aalysis of a Simple Closed Loop Supply Chai Arka Ghosh, Sarah M. Rya, Lizhi Wag, ad Aada Weerasighe April 8, 2 Abstract We cosider a closed loop supply chai where ew products are produced

More information

Installment Joint Life Insurance Actuarial Models with the Stochastic Interest Rate

Installment Joint Life Insurance Actuarial Models with the Stochastic Interest Rate Iteratioal Coferece o Maagemet Sciece ad Maagemet Iovatio (MSMI 4) Istallmet Joit Life Isurace ctuarial Models with the Stochastic Iterest Rate Nia-Nia JI a,*, Yue LI, Dog-Hui WNG College of Sciece, Harbi

More information

CME 302: NUMERICAL LINEAR ALGEBRA FALL 2005/06 LECTURE 8

CME 302: NUMERICAL LINEAR ALGEBRA FALL 2005/06 LECTURE 8 CME 30: NUMERICAL LINEAR ALGEBRA FALL 005/06 LECTURE 8 GENE H GOLUB 1 Positive Defiite Matrices A matrix A is positive defiite if x Ax > 0 for all ozero x A positive defiite matrix has real ad positive

More information

Lecture 4: Cauchy sequences, Bolzano-Weierstrass, and the Squeeze theorem

Lecture 4: Cauchy sequences, Bolzano-Weierstrass, and the Squeeze theorem Lecture 4: Cauchy sequeces, Bolzao-Weierstrass, ad the Squeeze theorem The purpose of this lecture is more modest tha the previous oes. It is to state certai coditios uder which we are guarateed that limits

More information

A Constant-Factor Approximation Algorithm for the Link Building Problem

A Constant-Factor Approximation Algorithm for the Link Building Problem A Costat-Factor Approximatio Algorithm for the Lik Buildig Problem Marti Olse 1, Aastasios Viglas 2, ad Ilia Zvedeiouk 2 1 Ceter for Iovatio ad Busiess Developmet, Istitute of Busiess ad Techology, Aarhus

More information

4.3. The Integral and Comparison Tests

4.3. The Integral and Comparison Tests 4.3. THE INTEGRAL AND COMPARISON TESTS 9 4.3. The Itegral ad Compariso Tests 4.3.. The Itegral Test. Suppose f is a cotiuous, positive, decreasig fuctio o [, ), ad let a = f(). The the covergece or divergece

More information

Capacity of Wireless Networks with Heterogeneous Traffic

Capacity of Wireless Networks with Heterogeneous Traffic Capacity of Wireless Networks with Heterogeeous Traffic Migyue Ji, Zheg Wag, Hamid R. Sadjadpour, J.J. Garcia-Lua-Aceves Departmet of Electrical Egieerig ad Computer Egieerig Uiversity of Califoria, Sata

More information

Efficient tree methods for pricing digital barrier options

Efficient tree methods for pricing digital barrier options Efficiet tree methods for pricig digital barrier optios arxiv:1401.900v [q-fi.cp] 7 Ja 014 Elisa Appolloi Sapieza Uiversità di Roma MEMOTEF elisa.appolloi@uiroma1.it Abstract Adrea igori Uiversità di Roma

More information

Log-Logistic Software Reliability Growth Model

Log-Logistic Software Reliability Growth Model Log-Logistic Software Reliability Growth Model Swapa S. Gokhale ad Kishor S. Trivedi 2y Bours College of Egg. CACC, Dept. of ECE Uiversity of Califoria Duke Uiversity Riverside, CA 9252 Durham, NC 2778-29

More information

Convex Bodies of Minimal Volume, Surface Area and Mean Width with Respect to Thin Shells

Convex Bodies of Minimal Volume, Surface Area and Mean Width with Respect to Thin Shells Caad. J. Math. Vol. 60 (1), 2008 pp. 3 32 Covex Bodies of Miimal Volume, Surface Area ad Mea Width with Respect to Thi Shells Károly Böröczky, Károly J. Böröczky, Carste Schütt, ad Gergely Witsche Abstract.

More information