MatLab实现数字信号处理：刘树堂解析

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"《Digital Signal Processing using MatLab》是由刘树堂教授翻译的，原作者是维纳.K.英格尔和约翰.G普罗克斯。这本书配合MATLAB代码，旨在帮助学生和学习者通过实践来掌握数字信号处理的知识。" 在数字信号处理领域，MATLAB是一种非常重要的工具，它为复杂计算和算法实现提供了简洁易用的环境。本书《Digital Signal Processing using MatLab》深入浅出地介绍了如何利用MATLAB进行数字信号处理的学习和应用。作者维纳.K.英格尔和约翰.G普罗克斯是该领域的专家，他们的著作通常具有权威性和实用性。刘树堂教授的翻译则确保了内容对中国读者的友好性和理解度。书中强调了问题解决在学习过程中的核心地位，无论是在课堂、自学小组还是个人独立学习，学生们通过解决实际问题来最有效地吸收知识。尤其在计算机科学和工程学科中，这种方法尤为重要。"ABCNOTE"部分指出，通过解答问题，学生可以更好地把握关键概念，这比长篇的解释更有效。问题解答提供了解决问题的方法，评估新知识的方式，以及体验现实问题的途径。最重要的是，它们鼓励学生积极参与到学习过程中。 BookWare Companion Series是一套旨在满足计算密集型问题解决需求的计算机辅助学习工具。这套系列的创立基于教师们的共识，即学生主动参与式的学习方式效果最佳。同时，教材应该与时俱进，跟上技术发展的步伐，满足现代教育的需求。MATLAB作为强大的计算平台，为数字信号处理的教学和学习提供了理想的实践平台。在《Digital Signal Processing using MatLab》中，读者将学习到如何使用MATLAB进行信号的采样、量化、滤波、频谱分析、变换等基本操作，同时也会接触到高级主题，如数字滤波器设计、傅立叶变换的应用、时频分析等。这些知识对于通信工程、音频处理、图像处理、生物医学信号分析等领域至关重要。通过实际编程和案例研究，读者不仅能掌握理论，还能提升解决实际问题的能力。

one of the finite number of

values

at specific instances in time,

and

hence

it can be represented by binary numbers,

bits. The processing of digital

signals

called DSP; in block diagram form it

represented by

Eguivalent

Analog

Processor

Discrete

System

where the various block elements are discussed below.

PrF:

This is a prefilter

an antialiasing filter, which conditions the

analog signal to prevent aliasing.

ADC:

This is called an analog-to-digital converter, which produces a

stream of binary numbers from analog signals.

Digital

signal

processor:

This is the heart of

DSP

and can represent

general-purpose computer or a special-purpose processor,

digital hard-

ware, and

on.

DAC:

This

the inverse operation to the ADC, called a digital-to-analog

converter, which produces a staircase waveform from a sequence of binary

numbers, a first step towards producing an analog signal.

PoF:

This is a postfilter to smooth out staircase waveform into the de-

sired analog signal

appears

from

the

above

two

approaches

signal

processing, analog

and digital, that the DSP approach is the more complicated, containing

more components than the “simpler looking” ASP. Therefore one might

ask

question: Why process signals digitally? The answer lies in many

advantages offered by DSP.

ADVANTAGES

DSP

OVER

ASP

major drawback of ASP is its limited scope for performing complicated

signal processing applications. This translates into nonflexibility in pro-

cessing and complexity in system designs. All of these generally lead to

expensive products. On the other hand, using a DSP approach, it

pos-

sible to convert an inexpensive personal computer into a powerful signal

processor. Some important advantages of DSP are these:

Systems using the DSP approach can be developed using software

running on a general-purpose csmputer. Therefore DSP

relatively con-

venient to develop and test, and the software

portable.

DSP operations are based solely on additions and multiplications,

leading to extremely stable processing capability-for example, stability

independent of temperature.

Ovetview

Digital

Signal

Prtxessing

In some applications, such

voice synthesis, a signal is first analyzed

to study its characteristics, which are then

used

in digital filtering to

generate a synthetic voice.

In the first half of this book we will deal with the signal-analysis

aspect of DSP. In Chapter

we will begin with basic descriptions of

discretetime signals and systems. These signals and systems are analyzed

in the frequency domain in Chapter

generalization of the frequency-

domain description, called the t-transform, is introduced in Chapter

The practical algorithms for computing the Fourier transform are dis-

cussed in Chapter

in the form of the discrete Fourier transform and the

fast Fourier transform.

The second half of this book is devoted to the signal-filtering aspect

DSP. In Chapter

we describe various implementations and structures of

digital filters. In Chapter

we provide design techniques and algorithms

for designing one type of digital filter called finitsduration impulse re-

sponse (or

FIR)

filters, while in Chapter

we provide a similar treatment

for another type of filter called infiniteduration impulse response (or IIR)

filters. In both chapters we discuss only the simpler but practically

use-

ful techniques of filter design. More advanced techniques are not covered.

Finally, the last two chapters provide some practical applications in the

form of projects that can be done using material learned in the first eight

chapters. In Chapter

concepts in adaptive filtering are introduced, and

simple projects in system identification, interference suppression, adap

tive line enhancement, and

forth are discussed. In Chapter

a brief

introduction to digital communications is presented with projects in such

topics

PCM, DPCM, and LPC being outlined.

In all these chapters the central theme

the generous use and ad-

equate demonstration of

MATLAB

tools. Most of the existing

MATLAB

functions for DSP are described in detail, and their correct use is demon-

strated

many examples. Furthermore, many new MATLAB functions are

developed to provide insights into the working of many algorithms. We

believe that this “hand-holding” approach will enable students to dispel

fears about DSP and will provide an enriching learning experience.

FEW WORDS

ABOUT

MATLAB@

MATLAB is an interactive, matrix-based system for scientific and engi-

neering numeric computation and visualization. Its strength lies in the

fact that complex numerical problems can be solved easily and in a frac-

tion of the time required with a programming language such

Fortran

or C. It

also powerful in the sense that by using its relatively simple

programming capability,

MATLAB

can be easily extended to create new

commands and functions.

Few

Words

about

MATLAB

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