Multimedia Signal Processing Theory and Applications in Speech, Music and Communications

Multimedia Signal Processing is a comprehensive and accessible text to the theory and applications of digital signal processing (DSP).  The applications of DSP are pervasive and include multimedia systems, cellular communication, adaptive network management, radar, pattern recognition, medical signal processing, financial data forecasting, artificial intelligence, decision making, control systems and search engines.

This book is organised in to three major parts making it a coherent and structured presentation of the theory and applications of digital signal processing. A range of important topics are covered in basic signal processing, model-based statistical signal processing and their applications.

Part 1: Basic Digital Signal Processing gives an introduction to the topic, discussing sampling and quantization, Fourier analysis and synthesis, Z-transform, and digital filters.

Part 2: Model-based Signal Processing covers probability and information models, Bayesian inference, Wiener filter, adaptive filters, linear prediction hidden Markov models and independent component analysis.

Part 3: Applications of Signal Processing in Speech, Music and Telecommunications explains the topics of speech and music processing, echo cancellation, deconvolution and channel equalization, and mobile communication signal processing.

• Covers music signal processing, explains the anatomy and psychoacoustics of hearing and the design of MP3 music coder
• Examines speech processing technology including speech models, speech coding for mobile phones and speech recognition
• Covers single-input and multiple-inputs denoising methods, bandwidth extension and the recovery of lost speech packets in applications such as voice over IP (VoIP)
• Illustrated throughout, including numerous solved problems, Matlab experiments and demonstrations
• Companion website features Matlab and C++ programs with electronic copies of all figures.

This book is ideal for researchers, postgraduates and senior undergraduates in the fields of digital signal processing, telecommunications and statistical data analysis. It will also be a valuable text to professional engineers in telecommunications and audio and signal processing industries.

Saeed Vaseghi is Professor of Communications and Signal Processing at Brunel University’s Department of Electronics and Computer Engineering and is Group Leader for the Communications & Multimedia Signal Processing Group. Previously, Saeed obtained a first in Electrical and Electronics Engineering from Newcastle University, and a PhD in Digital Signal Processing from Cambridge University.
His PhD in noisy signal restoration led to establishment of CEDAR, the world's leading system for restoration of audio signals. Saeed also held a British Telecom lectureship at UEA Norwich, and a readership at Queen's University of Belfast before his move to Brunel.