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Signal processing in electronic communications: For engineers and mathematiciansM J Chapman, D P Goodall and N C Steele, University of Coventry, UK
Woodhead Publishing Series in Electronic and Optical Materials No. 2
Comprehensive: elegantly demonstrates the mathematics for creating or designing signal processing networks.
Kybernetica
- deals with signal processing as an important aspect of electronic communications in its role of transmitting information, and the language of its expression
- topics considered include a speech production model, linear predictive filters, lattice filters and cepstral analysis, with application to recognition of non-nasal voiced speech and formant estimation
This text deals with signal processing as an important aspect of electronic communications in its role of transmitting information, and the language of its expression. It develops the required mathematics in an interesting and informative way, leading to confidence on the part of the reader. The first part of the book focuses on continuous-time models, and contains chapters on signals and linear systems, and on system responses. Fourier methods, so vital in the study of information theory, are developed prior to a discussion of methods for the design of analogue filters. The second part of the book is directed towards discrete-time signals and systems. There is full development of the z- and discrete Fourier transforms to support the chapter on digital filter design.
All preceding material in the book is drawn together in the final chapter on some important aspects of speech processing which provides an up-to-date example of the use of the theory. Topics considered include a speech production model, linear predictive filters, lattice filters and cepstral analysis, with application to recognition of non-nasal voiced speech and formant estimation.
In addition to course requirement for undergraduates studying electrical engineering, applied mathematics, and branches of computer science involving such signal processing as speak synthesis, computer vision and robotics, this book should provide a valuable reference source for post-graduate research work in industry and academia.
An elementary knowledge of algebra (e.g. partial fractions) is a prerequisite, and also calculus including differential equations. A knowledge of complex numbers and of the basic concept of a function of a complex variable is also needed.
ISBN 1 898563 30 6
ISBN-13: 978 1 898563 30 3
June 1997
310 pages 234 x 173mm paperback
£50.00 / US$85.00 / €60.00
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About the authors
Michael J Chapman, David P Goodall and Nigel C Steele, University of Coventry, UK
Titles which may also be of interest:
Digital filters and signal processing in electronic engineering
Digital image processing
Digital signal processing
Contents
Signals and linear system fundamentals
- Introduction
- Signals and systems
- L circuits
- Linear systems
- Simulation diagrams
- The Laplace transform
- Introduction to generalized functions
- Some properties of the Laplace transform
- Application to time linear systems
- Transfer functions
- Exercises
System responses
- Introduction
- Stability of linear time-invariant systems
- The impulse response
- The step response
- Signal decomposition and convolution
- Frequency response
- Exercises
System responses
- Introduction
- Stability of linear time-invariant systems
- The impulse response
- The step response
- Signal decomposition and convolution
- Frequency response
- Exercises
Fourier methods
- Introduction
- Fourier series
- The Fourier transform
- The Fourier spectrum
- Properties of the Fourier transform
- Signal energy and power
- A generalization of the Fourier transform
- The convolution theorems
- Sampling of time signals and its implications
- Exercises
Fourier methods
- Introduction
- Fourier series
- The Fourier transform
- The Fourier spectrum
- Properties of the Fourier transform
- Signal energy and power
- A generalization of the Fourier transform
- The convolution theorems
- Sampling of time signals and its implications
- Exercises
Analogue filters
- Introduction
- Analogue filter types
- A class of low filters
- Butterworth filters, the general case
- Filter transformations
- Other filter designs
- Exercises
Analogue filters
- Introduction
- Analogue filter types
- A class of low filters
- Butterworth filters, the general case
- Filter transformations
- Other filter designs
- Exercises
Discrete-time signals and systems
- Introduction
- Sequences
- Linear systems
- Simulation diagrams
- The z-transform
- Properties of the z-transform
- Application to linear time-invariant systems
- The z-transfer function
- A connection with the Laplace transform
- Exercises
Discrete-time signals and systems
- Introduction
- Sequences
- Linear systems
- Simulation diagrams
- The z-transform
- Properties of the z-transform
- Application to linear time-invariant systems
- The z-transfer function
- A connection with the Laplace transform
- Exercises
Discrete-time system responses
- Introduction
- BIBO and marginal stability
- The impulse response
- The step response
- Discrete-time convolution
- The frequency response
- Exercises
Discrete-time system responses
- Introduction
- BIBO and marginal stability
- The impulse response
- The step response
- Discrete-time convolution
- The frequency response
- Exercises
Discrete-time Fourier analysis
- Introduction
- The discrete Fourier transform, (DFT)
- The discrete-time Fourier transform, DTFT
- Estimating the DTFT
- Estimating Fourier series
- Estimating Fourier transforms
- The fast Fourier transform
- Exercises
Discrete-time Fourier analysis
- Introduction
- The discrete Fourier transform, (DFT)
- The discrete-time Fourier transform, DTFT
- Estimating the DTFT
- Estimating Fourier series
- Estimating Fourier transforms
- The fast Fourier transform
- Exercises
The design of digital filters
- Introduction
- The impulse invariant method
- The step invariant method
- The Bilinear transform method
- A direct’ design method: the Fourier series approach
- Windows
- Exercises
The design of digital filters
- Introduction
- The impulse invariant method
- The step invariant method
- The Bilinear transform method
- A direct’ design method: the Fourier series approach
- Windows
- Exercises
Aspects of speech processing
- Introduction
- Speech production model
- Correlation functions
- Linear predictive filters
- Estimation of the gain parameter
- Formant estimation
- Lattice filter formulation
- The cepstrum
- Homomorphic: systems and deconvolution
- Cepstral analysis of speech signals
- Form ant estimation using cepstral analysis
- Exercises
Aspects of speech processing
- Introduction
- Speech production model
- Correlation functions
- Linear predictive filters
- Estimation of the gain parameter
- Formant estimation
- Lattice filter formulation
- The cepstrum
- Homomorphic: systems and deconvolution
- Cepstral analysis of speech signals
- Form ant estimation using cepstral analysis
- Exercises
The complex exponential
The complex exponential
Linear predictive coding algorithms
Linear predictive coding algorithms
Answers to the exercises
Answers to the exercises
References