[内容简介]

The principles of signal processing are fundamental to the operation of everyday devices such as digital cameras, mobile telephones and digital audio players. This book introduces the basic theory of digital signal processing, placing a strong emphasis on the use of techniques in real-world applications. The author uses intuitive arguments rather than mathematical ones wherever possible, reinforced by practical examples and diagrams.

The first part of the book covers sampling, quantisation, the Fourier transform, filters, Bayesian methods and numerical considerations. These ideas are then developed in the second part, illustrating how they are used in audio, image, and video processing and compression, and in communications. The book concludes with methods for the efficient implementation of algorithms in hardware and software. Throughout, links between various signal processing techniques are stressed and real-world examples showing the advantages and disadvantages of the different approaches are presented enabling the reader to choose the best solution to a given problem. With over 200 illustrations and oven 30 exercises (including solutions), this book will appeal to practitioners working in any branch of signal processing, as well as to undergraduate students of electrical and computer engineering.

[目录]

Preface     ix
Foundations     1
Introduction     3
What is a signal?     3
Domain and range of a signal     3
Converting signals from one form to another     4
Processing signals     5
Notation     6
Sampling     10
Regular sampling     10
What is lost in sampling?     11
Examples of aliasing     13
Negative frequencies     15
The Nyquist limit     16
Irregular sampling     17
Conversion between analogue and digital     25
A simple digital signal processing system     25
Non-linear quantisation     28
How many bits do we need?     29
Dither     30
Non-ideal conversion     32
The frequency domain     37
Measuring rotational speed     37
More complicated motion     39
Interpreting the Fourier transform     42
How many Fourier coefficients are there?     43
Reconstructing a signal from its Fourier transform     43
Real signals     44
Dealing with non-periodic signals     49
The fast Fouriertransform     53
Filters     63
Smoothing a signal     63
Analysing a filter     66
Convolution in the frequency domain     74
Correlation     76
Designing FIR filters     77
Interpolation     83
Infinite impulse response filters     94
Filtering complex sequences     100
Likelihood methods     104
Probability and conditional probability     104
Probability and signal processing     109
Noise     111
Numerical considerations     124
Fixed-point representations     124
Negative numbers in fixed-point representations     135
Floating-point representations     139
Choosing between fixed point and floating point     143
Applications     147
Audio     149
The ear     149
Sample rates and conversion     149
Audio in the frequency domain     152
Compression of audio signals     154
Pitch extraction     163
Delta-sigma conversion     172
Still images     178
Luminance and chrominance     178
Gamma      179
An image as a signal     180
Filtering an image     185
The discrete cosine transform     193
JPEG compression for continuous-tone images     198
The discrete wavelet transform     202
Image scaling     209
Image enhancement     213
Edge detection     215
Processing of bilevel images     217
Pattern recognition     223
Moving images     231
Standard video formats     231
Deinterlacing     234
Standards conversion     239
Motion estimation     241
MPEG-2 video compression     246
Communications     253
Amplitude modulation     254
Frequency modulation     260
Quadrature amplitude modulation     263
Spread spectrum schemes     287
Implementations     299
Software implementations     300
Processor architectures     302
Hardware implementations     307
Bit-serial arithmetic     313
Answers     323
Index     329