Издательство Springer, 2008, -203 pp.
The field known as digital signal processing (DSP) has its roots in the 1940sand 1950s, and got started in eaest in the 1960s [10]. As DSP deals with how computers can be used to process signals, it should come as no surprise that the field’s growth parallels the growth in the use of the computer. The mode development of the Fast Fourier Transform in 1965 gave the field a great push forward. Since the 1960s, the field has grown by leaps and bounds. In this book, the reader is introduced to the theory and practice of digital signal processing. Much time is spent acquainting the reader with the mathematics and the insights necessary to master this subject. The mathematics is presented as precisely as possible; the text, however, is meant to be accessible to a third- or fourth-year student in an engineering program.
Several different aspects of the digital signal processing problem are considered. Part I deals with the analysis of discrete-time signals. First, the effects of sampling and of time-limiting a signal are considered. Next, the spectral analysis of signals is considered. Both the DFT and the FFT are considered, and their properties are developed to the point where the reader will understand both their mathematical content and how they can be used in practice.
After discussing spectral analysis and very briefly considering the spectral analysis of random signals, we move on to Part II. We take a break from the most mathematical parts of DSP, and we consider how one takes an analog signal and converts it into a digital one and how one takes a digital signal and converts it into an analog signal. We present many different types of converters in moderate depth.
After this tour of analog to digital and digital to analog converters, we move on to the third part of the book—and consider the design and analysis of digital filters. The Z-transform is developed carefully and then the properties, advantages, and disadvantages of infinite impulse response (IIR) and finite impulse response (FIR) filters are explained.
Over the last several years, MATLAB and Simulink have become ubiquitous in the engineering world. They are generally good tools to use when one wants to analyze and implement the mathematical techniques of signal processing. They are used throughout this book as tools of analysis and as platforms for designing, implementing, and testing algorithms.
Throughout the book, MATLAB and Simulink are used to allow the reader to experience DSP. It is hoped that in this way the beautiful mathematics presented will be seen to be part of a practical engineering discipline.
The Analog Devices ADuC841 is used to introduce the practical microprocessor-oriented parts of digital signal processing. Many chapters contain ADuC841-based laboratories—as well as traditional exercises. The ADuC841is an easy to use and easy to understand, 8052-based microcontroller (or microconverter, to use Analog Devices’ terminology). It is, in many ways, an ideal processor for student use. It should be easy to transpose the ADuC841-based laboratories to other microprocessors.
It is assumed that the reader is familiar with Fourier series and transforms and has some knowledge of signals and systems. Some acquaintance with probability theory and the theory of functions of a (single) complex variable will allow the reader to use this text to best advantage.
After reading this book, the reader will be familiar with both the theoryand practice of digital signal processing. It is to be hoped that the reader will lea to appreciate the way that the many elegant mathematical results presented form the core of an important engineering discipline.
The Analysis of Discrete-time Signals.
Understanding Sampling.
Signal Reconstruction.
Time-limited Functions Are Not Band-limited.
Fourier Analysis and the Discrete Fourier Transform.
Windowing.
Signal Generation with the Help of MATLAB.
The Spectral Analysis of Random Signals.
Analog to Digital and Digital to Analog Converters.
The General Structure of Sampled-data Systems.
The Operational Amplifier: An Overview.
A Simple Digital to Analog Converter.
The Binary Weighted DAC.
The R-2R Ladder DAC.
The Successive Approximation Analog to Digital Converter.
The Single- and Dual-slope Analog to Digital Converters.
The Pipelined A/D.
Resistor-chain Converters.
Sigma–Delta Converters.
Digital Filters.
Discrete-time Systems and the Z-transform.
Filter Types.
When to Use C (Rather than Assembly Language.
Two Simple FIR Filters.
Very-narrow-band Filters.
Design of IIR Digital Filters: The Old-fashioned Way.
New Filters from Old.
mplementing an IIR Digital Filter.
R Filter Design Using MATLAB.
Group Delay and Phase Delay in Filters.
Design of FIR Filters.
Implementing a Hilbert Filter.
The Goertzel Algorithm.
The field known as digital signal processing (DSP) has its roots in the 1940sand 1950s, and got started in eaest in the 1960s [10]. As DSP deals with how computers can be used to process signals, it should come as no surprise that the field’s growth parallels the growth in the use of the computer. The mode development of the Fast Fourier Transform in 1965 gave the field a great push forward. Since the 1960s, the field has grown by leaps and bounds. In this book, the reader is introduced to the theory and practice of digital signal processing. Much time is spent acquainting the reader with the mathematics and the insights necessary to master this subject. The mathematics is presented as precisely as possible; the text, however, is meant to be accessible to a third- or fourth-year student in an engineering program.
Several different aspects of the digital signal processing problem are considered. Part I deals with the analysis of discrete-time signals. First, the effects of sampling and of time-limiting a signal are considered. Next, the spectral analysis of signals is considered. Both the DFT and the FFT are considered, and their properties are developed to the point where the reader will understand both their mathematical content and how they can be used in practice.
After discussing spectral analysis and very briefly considering the spectral analysis of random signals, we move on to Part II. We take a break from the most mathematical parts of DSP, and we consider how one takes an analog signal and converts it into a digital one and how one takes a digital signal and converts it into an analog signal. We present many different types of converters in moderate depth.
After this tour of analog to digital and digital to analog converters, we move on to the third part of the book—and consider the design and analysis of digital filters. The Z-transform is developed carefully and then the properties, advantages, and disadvantages of infinite impulse response (IIR) and finite impulse response (FIR) filters are explained.
Over the last several years, MATLAB and Simulink have become ubiquitous in the engineering world. They are generally good tools to use when one wants to analyze and implement the mathematical techniques of signal processing. They are used throughout this book as tools of analysis and as platforms for designing, implementing, and testing algorithms.
Throughout the book, MATLAB and Simulink are used to allow the reader to experience DSP. It is hoped that in this way the beautiful mathematics presented will be seen to be part of a practical engineering discipline.
The Analog Devices ADuC841 is used to introduce the practical microprocessor-oriented parts of digital signal processing. Many chapters contain ADuC841-based laboratories—as well as traditional exercises. The ADuC841is an easy to use and easy to understand, 8052-based microcontroller (or microconverter, to use Analog Devices’ terminology). It is, in many ways, an ideal processor for student use. It should be easy to transpose the ADuC841-based laboratories to other microprocessors.
It is assumed that the reader is familiar with Fourier series and transforms and has some knowledge of signals and systems. Some acquaintance with probability theory and the theory of functions of a (single) complex variable will allow the reader to use this text to best advantage.
After reading this book, the reader will be familiar with both the theoryand practice of digital signal processing. It is to be hoped that the reader will lea to appreciate the way that the many elegant mathematical results presented form the core of an important engineering discipline.
The Analysis of Discrete-time Signals.
Understanding Sampling.
Signal Reconstruction.
Time-limited Functions Are Not Band-limited.
Fourier Analysis and the Discrete Fourier Transform.
Windowing.
Signal Generation with the Help of MATLAB.
The Spectral Analysis of Random Signals.
Analog to Digital and Digital to Analog Converters.
The General Structure of Sampled-data Systems.
The Operational Amplifier: An Overview.
A Simple Digital to Analog Converter.
The Binary Weighted DAC.
The R-2R Ladder DAC.
The Successive Approximation Analog to Digital Converter.
The Single- and Dual-slope Analog to Digital Converters.
The Pipelined A/D.
Resistor-chain Converters.
Sigma–Delta Converters.
Digital Filters.
Discrete-time Systems and the Z-transform.
Filter Types.
When to Use C (Rather than Assembly Language.
Two Simple FIR Filters.
Very-narrow-band Filters.
Design of IIR Digital Filters: The Old-fashioned Way.
New Filters from Old.
mplementing an IIR Digital Filter.
R Filter Design Using MATLAB.
Group Delay and Phase Delay in Filters.
Design of FIR Filters.
Implementing a Hilbert Filter.
The Goertzel Algorithm.