Multimedia Digital Signal Processing

MODULE CODE

EE3052B

AIMS

To provide an understanding of the fundamental concepts, and the applications, of digital signal and information processing techniques in communication and multimedia systems.

OBJECTIVES / LEARNING OUTCOMES

Students should understand and be able to apply:

• time domain processing techniques and their applications;

• frequency domain methods, z-transform and its uses in design and analysis of digital systems;

• the concepts of time and frequency resolution, and bandwidth, and their applications in communication system design and analysis;

• design and implementation of digital FIR and IIR filters;

• applications of frequency transforms and digital filters in communication and multimedia systems;

• probability and statistical models;

• model-based signal processing methods;

• use of probability models in communications, multimedia and information processing.

SUBJECT

 MATTER

Part I:  Digital Signal Processing And Applications 

Introduction To DSP And Its Applications: Signals, systems, signal processing methodologies. Basic elements of a digital signal processing system. Applications in multimedia and communication systems.

Discrete-Time Domain Signals: Sampling and Quantisation. Sequence representation. Elementary discrete-time signals. The convolution sum, properties of convolution. Impulse response, relation to the frequency response. Difference equations.

Z Transform: Review of the direct z-Transform, relation to Laplace and Fourier transforms Region of convergence (ROC). The properties of the direct z-Transform. System transfer functions, all pole and all zero systems. Inversion of the direct z-Transform. Applications in system design and stability analysis.

Frequency Analysis Of Discrete-Time Signals: Review of the Fourier transform. The discrete Fourier transform (DFT). Time and frequency resolutions of a DFT, bandwidth. Use of windows in spectrum analysis. Efficient computation of the DFT: FFT. Discrete Cosine Transform. Applications in spectrogram, pattern analysis, MPEG audio, voice conversion, radar, speech coding, music processing, image compression.

Digital Filters Design: FIR filters and their linear phase properties. FIR filter design, windowing. IIR filter design with the bilinear transformation and pole-zero placement. Filterbank design. Applications: communication systems, audio graphic equalisers, Dolby systems, noise reduction, image processing

Part II:  Model-Based Signal Processing And Applications

Probability Models And Applications : Modelling chance processes, such as the odds in a game, or collision of the Earth with comets. The use of statistics in pattern modelling and decision-making. Random Processes, Time-varying and Time-invariant systems. Statistics of random process, mean, variance, correlation and covariance matrix. Probability models, Gaussian, Poisson and Markov. Application of probability models in noise processing, signal detection, radar, sonar, voice/image pattern recognition, and the modelling of the users demand in a communication  system.

Information Models: Entropy and information measures. The information content of written and spoken English and digital communication systems. Application of entropy in coding, transmission and information storage.

Correlation And Power Spectrum : Correlation and its applications in signal detection, classification and recognition. Matched filters and detectors. Power spectrum and its relation to correlation. Applications in communications, radar and sonar. Applications in speech/image pattern recognition.

Linear Prediction (Lp) Models: Introduction to LP models. Derivation of LP models. Applications in speech and video coding and recognition. Application in noise reduction. Application in change detection. Application in radar signal processing.

Adaptive Filters For Communication: Introduction to LMS filters. Line echo cancellation. Acoustic echo cancellation. Channel equalisation. Noise reduction.

INVITED LECTURES

Multimedia, Mobile Communications and Blue Tooth Technology

READING LIST 

ESSENTIAL READING

Introduction to Digital Signal Processing (3rd edition)

J G Proakis, D G ManolakisMacmillan, 1996

Discrete-Time Signal Processing (2nd edition)    A Oppenheim and R Schafer  Prentice–Hall, Englewood Cliffs, 1992

Discrete Random Signals and Statistical Signal Processing      Therrien C. W.