Course overview Processamento de sinais 2009/10 LEA

Transcription

1 Course overview Processamento de sinais 2009/10 LEA João Pedro Gomes Instituto Superior Técnico Processamento de sinais MEAer (IST) Course overview 1 / 19

2 Course overview Motivation: Key ideas and applications of signal processing Systems Transforms (time frequency) Sampling theorem (continuous-time discrete-time) Course syllabus Bibliography Evaluation/grading Processamento de sinais MEAer (IST) Course overview 2 / 19

3 Key ideas in signal processing A system acts on an input signal to produce an output signal input signal system output signal Processamento de sinais MEAer (IST) Course overview 3 / 19

4 Key ideas 2 Example (Continuous-time signal x(t), t R) Electrical current, pressure, temperature, etc. t Example (Discrete-time signal x(n), n Z) Samples of a continuous-time signal, symbols from a digital information source, etc n Processamento de sinais MEAer (IST) Course overview 4 / 19

5 Key ideas 3 continuous-time signal system continuous-time signal Typically implemented by an electrical circuit Continuous-time systems Fast Hard to implement nonlinear and time-varying operations Limited precision (component tolerance, etc.) High cost Processamento de sinais MEAer (IST) Course overview 5 / 19

6 Key ideas 4 discrete-time signal system discrete-time signal Our course emphasizes these systems! Usually implemented in software or programmable hardware Discrete-time signals Nonlinear and time-varying operations easily implemented Finite precision (practically unlimited in floating-point arithmetic) Easily modifiable (software/firmware upgrade) Slower Processamento de sinais MEAer (IST) Course overview 6 / 19

7 Key ideas 5 Key idea Signals are represented in the frequency domain using the Fourier transform (FT) {x[n] : n Z} F { X(e jω ) : ω [ π,π] } FT x[n] X(e jω ) Signal in time domain Signal in frequency domain x[n] X(e jω ) π 0 π Processamento de sinais MEAer (IST) Course overview 7 / 19

8 Key ideas 6 The FT explains a signal s spectral content x[n] X(e jω ) π 0 π π 0 π Processamento de sinais MEAer (IST) Course overview 8 / 19

9 Key ideas 7 The FT explains how a system acts in the frequency domain Example (Interference suppression) interference system π 0 π π 0 π Processamento de sinais MEAer (IST) Course overview 9 / 19

10 Key ideas 8 Example (Modulator) system π 0 π π 0 π Application Modulator + interference suppressor = frequency-domain multiplexing of digital communications signals Processamento de sinais MEAer (IST) Course overview 10 / 19

11 Key ideas 9 Key idea (Sampling) Subject to appropriate conditions, the sampling theorem states that a continuous signal can be regenerated from samples x(nt) : n Z Non-trivial result: E.g., below x(nt) = y(nt) but x(t) y(t) x(t) y(t) T t Processamento de sinais MEAer (IST) Course overview 11 / 19

12 Key ideas 10 Application (Sampling theorem) Compact discs Processing of continuous-time signals by discrete-time systems x(t) system y(t) x(t) C/D x[n] = x(nt) system y[n] = y(nt) D/C y(t) T T Processamento de sinais MEAer (IST) Course overview 12 / 19

13 Syllabus Discrete-time signals and systems (ch. 2) Z transform (ch. 3) Sampling of continuous-time signals (ch. 4) Transform analysis of LTI systems (ch. 5) Structures for discrete-time systems (ch. 6) Discrete Fourier transform (DFT) (ch. 8) Fast Fourier transform (FFT) algorithms (ch. 9) Fourier analysis of signals using the DFT (ch. 10) Filter design techniques (ch. 7) Processamento de sinais MEAer (IST) Course overview 13 / 19

14 Bibliography Main reference: Alan Oppenheim, Ronald Schafer, Discrete-Time Signal Processing, Prentice-Hall, 2nd ed., 1999 Supplementary material: Roberto Cristi, Modern Digital Signal Processing, Thomson Brooks/Cole, 2004 Isabel Lourtie, Sinais e Sistemas, Escolar Editora, 2002 Sanjit Mitra, Digital Signal Processing, McGraw-Hill, 2001 Boaz Porat, A Course in Digital Signal Processing, John Wiley & Sons, 1996 IEEE Signal Processing Magazine (applications in echo cancellation, radar, mobile communications, image compression, genomic signal processing, multimedia, speech processing, source separation, etc.) Processamento de sinais MEAer (IST) Course overview 14 / 19

15 Grading Exam Processamento de sinais MEAer (IST) Course overview 15 / 19

16 DSP topics Application (Audio) Acoustic room compensation Noise reduction, audio restoration and enhancement Sound compression (e.g., mp3), sound effects Acoustic echo cancellation for hands-free telephony Application (Speech) Speech analysis Speaker recognition Speech synthesis Speech enhancement Language processing Processamento de sinais MEAer (IST) Course overview 16 / 19

17 DSP topics Application (Image processing and multimedia) Image restoration and enhancement Image segmentation and 3D reconstruction Medical imaging (ultrasound, MRI, PET) Computer vision Image and video coding and transmission Human-computer interfaces Application (Remote sensing) Radar/sonar processing Synthetic-aperture radar and sonar Source localization, tracking and classification 3D reconstruction Processamento de sinais MEAer (IST) Course overview 17 / 19

18 DSP topics Application (Bioinformatics and systems biology) Analysis and annotation of genetic data Analysis and classification of microarray data Biological systems modeling Application (Telecommunications) Telephone, cable and wireline modems Wireless systems: Transmission over selective channels, network design, QoS MIMO and smart antennas Multiuser communication Wireless sensor networks Processamento de sinais MEAer (IST) Course overview 18 / 19

19 DSP topics Application (Instrumentation) High-performance A/D and D/A conversion Filter design Transient signal analysis Multiresolution analysis Feature extraction Detection and classification Performance bounds Data fusion Processamento de sinais MEAer (IST) Course overview 19 / 19