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Cheetham Aims: To gain an understanding of the significance of digital signal processing (DSP) in the fields of computing, telecommunications and other areas of Computer Science and Electronic/Electrical Engineering. To gain an appreciation of the technology and the software tools currently available and to study in detail some of the most important design techniques for DSP systems. Learning Outcomes:- After successfully completing this course students will be able to: understand the significance of digital signal processing in the fields of computing, telecommunications, multi-media technology and other areas of computer science and Electronic/Electrical Engineering. understand fundamental concepts such as 'linearity' , 'time-invariance', 'impulse response', 'convolution', 'frequency response', 'z-transforms' and the 'discrete time Fourier transform'. as applied to discrete time signal processing systems. apply a design technique for FIR type digital filters known as the "windowing method". apply several design techniques for IIR type digital filters: "pole-zero placement", the "derivative approximation" and the "bilinear transformation" techniques. use the "MATLAB" language and "signal processing toolboxes" for analysing, designing and implementing digital signal processing (DSP) systems such as digital filters. specify the "real time" implementation of DSP operations using special purpose fixed point 'DSP microprocessors'. understand analogue/digital conversion as required for the digital processing of analogue signals. understand the discrete Fourier transform (DFT), its applications and its implementation by FFT techniques. Assessment of Learning Outcomes: 2 hour written examination Contribution to programme learning outcomes: A2, A3, A5, B1, B2, B3, C4 Reading List and Supporting Material: S.W. Smith, "Scientist and Engineer's Guide to Digital Signal Processing " California Tech. Publishing, 2nd ed., 1999, available complete at: HYPERLINK "http://www.dspguide.com/"http://www.dspguide.com/ Dr. Cheetham's lecture notes from a similar course (EE3262) given last year available at:  HYPERLINK http://www.cs.man.ac.uk/~barry/mydocs/CS3291 http://www.cs.man.ac.uk/~barry/mydocs/CS3291 ] Syllabus: Section 1: Introduction (1 lecture): Definition of continuous time (analogue), discrete time and digital signals. Sampling and quantisation in general terms. Introduction to analogue and digital signal processing. Section 2: Brief review of analogue and digital signal processing systems (2 lectures): Transfer function and frequency-response of an analogue filter. Low-pass and band-pass analogue filters. Butterworth low-pass gain response approximation. Section 3: Discrete time linear time-invariant (LTI) signal processing systems (4 lectures) Recursive and non-recursive difference equations. Signal flow-graphs and their implementation by simple computer programs. Linearity, time invariance and impulse-response for discrete time systems. Definition of finite impulse response (FIR) and infinite impulse response (IIR) type digital filters. Stability and causality. Time-domain convolution. Frequency response as discrete time Fourier transform (DTFT) of impulse response. Gain and phase responses. Linear phase and group delay. Inverse DTFT. Use of MATLAB for analysing the frequency-response of digital filters. Section 4: Design of FIR digital filters (2 lectures) Design of FIR digital filters by the Fourier series approximation method. Implementation on personal computers and in real time on dsp chips. Effect of increasing order and use of non-rectangular windows. Alternative methods. Section 5: Introduction to z-transforms and IIR type discrete time filters (4 lectures) . System function, H(z), as z-transform of impulse response. Relationship between system function, difference equation, signal flow-graph and software implementation of FIR and IIR type digital filters. Poles and zeros. Distance rule for estimating the gain response of a digital filter from an Argand diagram (z-plane) of poles and zeros. Design of a digital IIR "notch" filter and a resononator by pole/zero placement. Application to these filters to sound recordings. Section 6: Design of IIR type digital filters using analogue filter approximations (3 lectures) Derivative approximation technique. Bilinear transformation method . Survey of alternative techniques. Section 7: Digital processing of analogue signals and other data (3 lectures) Sampling theory, aliasing, effect of quantisation and, sample and hold reconstruction. Oversampling to simplify analogue filters. Overall design of a digital system for processing analogue signals. Processing of other time-series. Section 8: Introduction to the discrete Fourier transform (DFT) (3 lectures) Derivation of DFT from DTFT. Inverse DFT. Effects of windowing and frequency domain sampling. Non-rectangular windows. Implementation of the DFT by the 'fast Fourier transform' algorithm (FFT) and speed comparison of direct DFT with FFT. Use of DFT and FFT for spectral estimation. Discussion of exercises and problems EE3271 Syllabus - PAGE 3-  DATE \@ "dd/MM/yy" 12/07/01 BMGC "'0=BKT_r†Ž˜ Хдсэѕџ +1ЊОПМ л м ћ ' E l y е з ћ ќ ! 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