Advanced Digital Signal Processing and Noise Reduction, 4th Edition

by Saeed V. Vaseghi (Brunel University)

• ISBN13: 9780470740163
• ISBN10: 0470740167
• Format: eBook
• Copyright: 2008-12-01
• Publisher: Wiley

Summary

Digital signal processing plays a central role in the development of modern communication and information processing systems. The theory and application of signal processing is concerned with the identification, modelling and utilisation of patterns and structures in a signal process. The observation signals are often distorted, incomplete and noisy and therefore noise reduction, the removal of channel distortion, and replacement of lost samples are important parts of a signal processing system.The fourth edition of Advanced Digital Signal Processing and Noise Reduction updates and extends the chapters in the previous edition and includes two new chapters on MIMO systems, Correlation and Eigen analysis and independent component analysis. The wide range of topics covered in this book include Wiener filters, echo cancellation, channel equalisation, spectral estimation, detection and removal of impulsive and transient noise, interpolation of missing data segments, speech enhancement and noise/interference in mobile communication environments. This book provides a coherent and structured presentation of the theory and applications of statistical signal processing and noise reduction methods.Two new chapters on MIMO systems, correlation and Eigen analysis and independent component analysisComprehensive coverage of advanced digital signal processing and noise reduction methods for communication and information processing systemsExamples and applications in signal and information extraction from noisy data Comprehensive but accessible coverage of signal processing theory including probability models, Bayesian inference, hidden Markov models, adaptive filters and Linear prediction modelsAdvanced Digital Signal Processing and Noise Reduction is an invaluable text for postgraduates, senior undergraduates and researchers in the fields of digital signal processing, telecommunications and statistical data analysis. It will also be of interest to professional engineers in telecommunications and audio and signal processing industries and network planners and implementers in mobile and wireless communication communities.

Table of Contents

Symbols

Abbreviations

Introduction

Signals, Noise and Information

Signal Processing Methods

Applications of Digital Signal Processing

A Review of Sampling and Quantisation

Summary

Bibliography

Noise and Distortion

Introduction

White Noise

Coloured Noise; Pink Noise and Brown Noise

Impulsive and Click Noise

Impulsive and Click Noise

Thermal Noise

Shot Noise

Flicker (I/f) Noise

Burst Noise

Electromagnetic (Radio) Noise

Channel Distortions

Echo and Multi-path Reflections

Modelling Noise

Summary

Bibliography

Information Theory and Probability Models

Introduction: Probability and Information Models

Random Processes

Probability Models

Information Models

Stationary and Non-stationary Processes

Expected Values of a Process

Some Useful Classes of Random Processes

Transformation of a Random Process

Search Engines: Citation Ranking

Summary

Bibliography

Baseyian Inference

Bayesian Estimation Theory: Basic Definitions

Bayesian Estimation

The Estimate-Maximise Method

CramerûRao Bound on the Minimum Estimator Variance

Design of Gaussian Mixture Models

Bayesian Classification

Modeling the Space of a Random Process

Summary

Bibliography

Hidden Markov Models

Statistical Models for Non-Stationary Processes

Hidden Markov Models

Training Hidden Markov Models

Decoding of Signals Using Hidden Markov Models

HMM In DNA and Protein Sequence Modelling

HMMs for Modelling Speech and Noise

Summary

Bibliography

Least Square Error Wiener-Kolmogorov Filters

Least Square Error Estimation: Wiener-Kolmogorov Filter

Block-Data Formulation of the Wiener Filter

Interpretation of Wiener Filters as Projection in Vector Space

Analysis of the Least Mean Square Error Signal

Formulation of Wiener Filters in the Frequency Domain

Some Applications of Wiener Filters

Implementation of Wiener Filters

Summary

Bibliography

Adaptive Filters, Kalman, RLS, LMS

Introduction

State-Space Kalman Filter

Extended Kalman Filter

Unscented Kalman Filter

Sample-Adaptive Filters

Recursive Least Square(RLS) Adaptive Filters

The Steepest-Descent Method

The LMS Filter

Summary

Bibliography

Linear Prediction Models

Linear Prediction Coding

Forward, Backward and Lattice Predictors

Short-term and Long-Term Linear Predictors

MAP Estimation of Predictor Coefficients

Formant-Tracking LP Models

Sub-Band Linear Prediction

.i.Signal Restoration Using Linear Prediction Models

Summary

Bibliography

Eigenvalue Analysis and Principal Component Analysis

Introduction

Eigen Analysis

Principal Component Analysis

Summary

Bibliography

Power Spectrum Analysis

Power Spectrum and Correlation

Fourier Series: Representation of Periodic Signals

Energy-Spectral Density and Power-Spectral Density

Fourier Transform: Representation of Aperiodic Signals

Non-Parametric Power Spectrum Estimation

Model-Based Power Spectral Estimation

High Resolution Spectral Estimation Based on Subspace Eigen-Analysis

Summary

Bibliography

Interpolation û Replacement of Lost Samples

Introduction

Model-Based Interpolation

Model-Based Interpolation

Summary

Bibliography

Signal Enhancement via Spectral Amplitude Estimation

12.1Introduction

Spectral Representation of Noisy Signals

Vector Representation of Spectrum of Noisy Signals

Spectral Subtraction

Bayesian MMSE Spectral Amplitude Estimation

Estimation of Signal to Noise Ratios

Application to Speech Restoration and Recognition

Summary

Bibliography

Impulsive Noise: Modelling, Detection and Removal

Impulsive Noise

Autocorrelation and Power Spectrum of Impulsive Noise

Probability Models for Impulsive Noise

Impulse contamination, Signal to Impulsive Noise Ratio

Median Filters

Impulsive Noise Removal Using Linear Prediction Models

Robust Parameter Estimation

Restoration of Archived Gramophone Records

Summary

Bibliography

Transient Noise Pulses

Transient Noise Waveforms

Transient Noise Pulse Models

Detection of Noise Pulses

Removal of Noise Pulse Distortions

Summary

Bibliography

Echo Cancellation

Introduction: Acoustic and Hybrid.i.Hybrid Echoes

Echo Return Time: The Sources of Delay in Communication Networks

Telephone Line Hybrid Echo

Hybrid Echo Suppression

.i.Adaptive Echo Cancellation

Acoustic .i.Echo

.i.Sub-band Acoustic Echo Cancellation

.i. Echo Cancellation with Linear Prediction Pre-whitening

Multiple-Input Multiple-Output (MIMO) Acoustic Echo Cancellation

Summary

Bibliography

Channel Equalisation and Blind Deconvolution

Introduction

Blind-Deconvolution Using Channel Input Power Spectrum

Equalisation Based on Linear Prediction Models

Bayesian Blind Deconvolution and Equalisation

Blind Equalisation for Digital Communication Channels

Equalisation Based on Higher-Order Statistics

Summary

Bibliography

Speech Enhancement: Noise Reduction, Bandwidth Extension and Packet Replacement

An Overview of Speech Enhancement in Noise

Single-Input Speech Enhancement Methods

Speech Bandwidth Extension

Interpolation of Lost Speech Segments

Multiple-Input Speech Enhancement Methods

Speech Distortion Measurements

Summary

Bibliography

Multiple-Input Multiple-Output Systems, Independent Component Analysis

Introduction

MIMO Signal Propagation and Mixing Models

Independent Component Analysis

Summary

Bibliography

Signal Processing in Mobile Communication

Introduction to Cellular Communication

Communication Signal Processing in Mobile Systems

Noise, Capacity and Spectral Efficiency

Multi-path and Fading in Mobile Communication

Smart Beam-forming Antennas

Summary

Bibliography

Index

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