Introduction to Fourier Series

Transcription

1 Introduction to Fourier Series A function f(x) is called periodic with period T if f(x+t)=f(x) for all numbers x. The most familiar examples of periodic functions are the trigonometric functions sin and cos which are periodic with period 2π. Under certain conditions, a periodic function f(x) can be represented as an infinite sum of sine and cosine terms (called a Fourier series expansion) as follows f(x)= A n=1 A n cos(nx)+ n=1 B n sin(nx) Dana Mackey (DIT) Maths 1 / 31

2 Example The sawtooth wave function has the form f(x)=x π x π f(x+2kπ)=f(x) for k =±1,±2,±3,... The Fourier series expansion for this function is ( x =2 sin(x) sin(2x) + sin(3x) ) 2 3 for π<x < π. Dana Mackey (DIT) Maths 2 / 31

3 Figure: The first term in the Fourier series expansion, x 2sin(x) Dana Mackey (DIT) Maths 3 / 31

4 Figure: The first 2 terms in the Fourier series expansion, x 2sin(x) sin(2x) Dana Mackey (DIT) Maths 4 / 31

5 Figure: The first 3 terms, x 2sin(x) sin(2x)+ 2 3 sin(3x) Dana Mackey (DIT) Maths 5 / 31

6 Figure: The first 4 terms, x 2sin(x) sin(2x)+ 2 3 sin(3x) 1 2 sin(4x) Dana Mackey (DIT) Maths 6 / 31

7 Remarks 1 The Fourier series expansion provides an approximation method: the more terms are selected in the series, the better the approximation 2 The Fourier series allows a periodic signal to be expressed in terms of simple sinusoidal oscillations 3 We have approximated the function f(x)=x for π<x < π in terms of sinusoidal terms so even non-periodic functions can have a Fourier series expansion! Dana Mackey (DIT) Maths 7 / 31

8 Even and odd functions A function f(x) is called even if f( x)=f(x) for all x (so its graph is symmetric with respect to the y-axis). A function f(x) is called odd if f( x)= f(x) for all x (so its graph is symmetric with respect to the origin). For example, cos(x) and even powers of x are even functions while sin(x) and odd powers of x are odd functions. The Fourier series for an even function contains only cos terms (B n =0 for all n), while the Fourier series of an odd function contains only sin terms (A n =0 for all n). Dana Mackey (DIT) Maths 8 / 31

9 Examples The sawtooth wave function is an odd function which has the expansion ( x 2 sin(x) sin(2x) + sin(3x) ) 2 3 for π<x < π. The function f(x)=x 2, π x π, together with its periodic extension, is an even function which has the expansion ( x 2 π2 3 4 cos(x) cos(2x) cos(3x) ) 3 2 Dana Mackey (DIT) Maths 9 / 31

10 Even and odd extensions Given a function f(x) defined on [0,π] we often need an expansion in sine terms (or cosine terms) only. To expand f(x) in cosine terms we make an even extension of the function from the interval [0,π] onto the interval [ π,0]. This will give us a function which is even on the interval [ π,π]. To expand f(x) in sine terms we make an odd extension of the function from the interval [0,π] onto the interval [ π,0]. This will give us a function which is odd on the interval [ π,π]. Dana Mackey (DIT) Maths 10 / 31

11 Even and odd extensions (a) Even extension (b) Odd extension Dana Mackey (DIT) Maths 11 / 31

12 Example Expand f(x)=1, 0 x π in sine series. Answer: 1 4 π ( sin(x)+ sin(3x) + sin(5x) ) Dana Mackey (DIT) Maths 12 / 31

13 Functions of period 2L It is often necessary to work with periodic functions with period other than 2π. The Fourier series for such functions is easily modified as f(x) A A n cos( πnx n=1 L )+ B n sin( πnx n=1 L ) where the coefficients are given as A 0 = 1 L L Lf(x)dx; A n = 1 L B n = 1 L L L L L f(x)sin( πnx L )dx f(x)cos( πnx L )dx; Dana Mackey (DIT) Maths 13 / 31

14 The complex form of a Fourier series Let f(x) be an integrable function on the interval [ π,π]. Its Fourier series can be written in complex form as where where n=0,±1,±2,... Also we have f(x) n= C n e inx C n = 1 π f(x)e inx dx 2π π C 0 = A 0 2 ; C n = A n ib n ; C n = A n+ ib n ; n> Dana Mackey (DIT) Maths 14 / 31

15 Note: The simplification from trigonometric form to exponential form makes use of the formula e iα =cos(α)+isin(α) Note: If f(x) is a real function then the coefficient C n is the complex conjugate of C n, for all n>0. Exercise: Calculate the complex Fourier series for the function f(x)=x in the interval 2 x 2. We find that x 2i( 1) n ( πinx exp n= nπ 2 n 0 ) Dana Mackey (DIT) Maths 15 / 31

16 The convergence of the Fourier series The Fourier series of a function f(x) of period 2π converges for all values of x. The sum of the series is equal to f(x), if x is a point of continuity for f(x); 1 2 [f(x+0)+f(x 0)] (the mean of left-hand and right-hand limits) if x is a point of discontinuity. The Fourier series is therefore a good approximation for the values of a function at all points where the function is continuous. Close to a point of discontinuity, the Fourier series approximation will overshoot the value of the function. This behaviour is known as the Gibbs phenomenon. Dana Mackey (DIT) Maths 16 / 31

17 Example Consider the square-wave function (black) represented below together with its Fourier series approximation (red): Figure: The first 3 terms, 1 4 π ( ) sin(x)+ sin(3x) 3 + sin(5x) 5 + Dana Mackey (DIT) Maths 17 / 31

18 Parseval s identity This formula relates a function f(x) to the coefficients of its Fourier series. If f is periodic with period 2π then we have 1 π f 2 (x)dx = π π n= C n 2 = A (A 2 n+bn) 2 n=1 where C n are the coefficients of the exponential Fourier series and A n, B n are the coefficients of the trigonometric Fourier series. Example: Using Parseval s identity and the Fourier series for the function f(x)=x 2 on [ 2,2], calculate the sum n=1 1 n 4. Dana Mackey (DIT) Maths 18 / 31

19 The Fourier transform Given a function f(x) (a time signal), we can define a new function F(s)= 1 2π f(x)e isx dx which is called the Fourier transform of f(x). The signal f(x) can be recovered from F(s) using the inverse Fourier transform: f(x)= 1 F(s)e isx dx 2π Dana Mackey (DIT) Maths 19 / 31

20 The Fourier transform In electrical engineering, a slightly different notation is used: F(s)= 1 f(x)e isx dx 2π In this context, the Fourier transform F(s) is also called the spectrum of the time signal f(x) and the new variable s denotes a frequency. The inverse Fourier transform is: f(x)= F(s)e isx dx Dana Mackey (DIT) Maths 20 / 31

21 Example The Fourier transform of the top-hat or gate function { 1 if x <1 f(x)= 0 if x >1 is equal to 1 2 F(s)= e isx sin(s) dx = 1 π s (a) Gate function (b) Fourier transform Dana Mackey (DIT) Maths 21 / 31

22 The Fourier transform can be regarded as a generalization of the Fourier series representation of a function. Recall the complex (exponential) Fourier series f(x) n= C n e inx where C n = 1 π f(x)e inx dx 2π π The Fourier transform replaces the infinite sum by an integral and the integer n becomes a continuous variable, s: f(x)= F(s)e isx dx and F(s)= 1 f(x)e isx dx 2π Dana Mackey (DIT) Maths 22 / 31

23 Sine and cosine Fourier transform We can also define the sine and cosine Fourier transforms (which represent continuous forms of the usual trigonometric series) using the formulas: Sine transform: Inverse sine transform: F S (s)= f(x)= 2 f(x)sin(sx)dx π 0 2 F S (s)sin(sx)ds π 0 Dana Mackey (DIT) Maths 23 / 31

24 Sine and cosine Fourier transform Cosine transform: F C (s)= Inverse cosine transform: f(x)= 2 f(x)cos(sx)dx π 0 2 F C (s)cos(sx)ds π 0 Dana Mackey (DIT) Maths 24 / 31

25 Existence of the Fourier transform In order to calculate a Fourier transform, the function f(x) must be defined on the whole real axis ( <x < ) and it must satisfy f(x) dx < This means that the function f(x) must be zero at ±. Example: Calculate the Fourier transform of the one-sided exponential function: { e x if x 0 f(x)= 0 if x <0 Dana Mackey (DIT) Maths 25 / 31

26 The unit step function The unit step function (or Heaviside function) is defined by { 1 if x >a H(x a)= 0 if x <a A combination of step functions can be used to denote a function which has a constant value over a limited range. For example, the function F(x)=3[H(x a) H(x b)] has the value 3 for a<x <b and 0 outside this interval. The step function can be used to denote a change from 0 to a different type of behaviour. For example, the one-sided exponential function, { e x if x 0 f(x)= = H(x) e x 0 if x <0 Dana Mackey (DIT) Maths 26 / 31

27 The Dirac delta function The Dirac delta function, δ(x), is defined by the properties δ(x)=0 for x 0 δ(x)dx =1 Similarly, we can define a delta function centred at a point x =a (different from zero) and denote this by δ(x a). The delta function is not a function in the classical sense so it is often referred to as a generalized function or a distribution. Dana Mackey (DIT) Maths 27 / 31

28 The delta function can also be defined as the limit of a sequence of functions which get progressively thinner and taller, for example, the gate functions: { n if 1 n (x)= 2n <x < 1 2n 0 otherwise =n [ H(x+ 1 2n ) H(x 1 ] 2n ) Dana Mackey (DIT) Maths 28 / 31

29 Properties of the delta function The fundamental property of the delta function is f(x)δ(x a)dx =f(a) where f(x) is any continuous function. The delta function can therefore be thought of as transforming a function f(x) into a number f(a) (where a is the centre of the delta function). We also have d H(x)= δ(x) dx (the delta function is the derivative of the unit step function). Dana Mackey (DIT) Maths 29 / 31

30 Fourier transform The Fourier transform of the delta function is F(s)= 1 2π e isx δ(x)dx = 1 2π. Hence, the delta function can be recovered from F(s) using the inverse Fourier transform: δ(x)= 1 e isx F(s)ds = 1 e isx ds 2π 2π which is an alternative representation for the delta function. Dana Mackey (DIT) Maths 30 / 31

31 Interpretation The Dirac delta function is used in physics to represent a point source. For example, the total electric charge in a finite volume V is given by Q = V ρ(x)dx where ρ(x) is the charge density. Now suppose a charge, Q, is concentrated at one point x =a. The charge density should be zero everywhere except at x =a where it should be infinite, seeing we have a finite charge in an infinitely small volume. Therefore Q = ρ(x)dx where ρ(x)=qδ(x a) V Dana Mackey (DIT) Maths 31 / 31