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

Description

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 coderContent: Chapter 1 Introduction (pages 1–24): Chapter 2 Fourier Analysis and Synthesis (pages 25–77): Chapter 3 z?Transform (pages 79–109): Chapter 4 Digital Filters (pages 111–153): Chapter 5 Sampling and Quantisation (pages 155–171): Chapter 6 Information Theory and Probability Models (pages 173–232): Chapter 7 Bayesian Inference (pages 233–274): Chapter 8 Least Square Error, Wiener–Kolmogorov Filters (pages 275–295): Chapter 9 Adaptive Filters: Kalman, RLS, LMS (pages 297–321): Chapter 10 Linear Prediction Models (pages 323–351): Chapter 11 Hidden Markov Models (pages 353–379): Chapter 12 Eigenvector Analysis, Principal Component Analysis and Independent Component Analysis (pages 381–413): Chapter 13 Music Signal Processing and Auditory Perception (pages 415–481): Chapter 14 Speech Processing (pages 483–525): Chapter 15 Speech Enhancement (pages 527–571): Chapter 16 Echo Cancellation (pages 573–590): Chapter 17 Channel Equalisation and Blind Deconvolution (pages 591–624): Chapter 18 Signal Processing in Mobile Communication (pages 625–642):