1st Edition
Applied Signal Processing Concepts, Circuits, and Systems
Classical signal processing techniques are based primarily on the analog nature of all signals. However, the continuously improving performance of digital circuitry and processors has prompted a switch to digital signal processing techniques rather than the traditional analog ones.
Applied Signal Processing recognizes the linkage between the two paradigms and presents a unified treatment of both subjects (analog and digital signal processing) in one authoritative volume. It introduces underlying principles, basic concepts, and definitions as well as classic and contemporary designs of signal processing systems. The author includes a detailed description of data converters, an interface between the real world of analog signals and the artificial world of digital signals. He provides a concise presentation of topics by limiting the number of complex equations and using lucid language. Numerous real-world application examples are featured within each chapter including architectures from Texas Instruments, Motorola, and Analog Devices.
With its compounded coverage of both analog and digital signal processing techniques, this book provides engineers with the knowledge they need to understand the analog basis of modern digital signal processing techniques and construct architectures for modern systems.
What are Signals?
Signal parameters
Why Signal processing?
Analog vs. Digital Signal processing
Practical Signal processing Systems
Analog Signal Processing
Amplitude Shaping
Frequency Spectrum Shaping
Phase Errors Correction
Waveform Generation
Analog Filter Design
Describing Equations
Design Procedures
Filter Specifications
Approximations to the Ideal Response
Realization
Practical RC-Filters Design
Switched Capacitor Filter Realization
Design examples
Data Converters
Introduction
A typical DSP System
Specifications of Data Converters
Sampling
Sample and Hold Circuits
Quantization
Basic Quantization Techniques
Digital to Analog Converters
Analog Comparators
Basic ADC Architectures
Practical High-Speed, High- Resolution ADC’s
Testing of Data Converters
Examples
Digital Signal Processing
Why Digital Signal processing?
Some Practical DSP Application Examples
Some Basic DSP Operations
The Z- Transform
Digital Filters
Digital Filter Design
Design Procedures
Design of FIR Filters
Approximations for FIR filters
The windowing Method
The Optimal Method
The Frequency Sampling Method
The Least Pth-norm Optimal Method
Realization Topologies
Design examples
Design of IIR Filters
Stability Test
Realization Topologies
Approximations for IIR filters
The Invariant-Impulse Response Method
The Bilinear Transform Method
The Least Pth-Norm Optimal Method
Effect of Finite Word Length Arithmetic
Multi-Rate Signal processing
Introduction
Decimation
Interpolation
Fractional sampling rate change
Cascaded decimation / interpolation
Discrete Transforms
The Discrete Fourier Transform
The Inverse Fourier Transform
Properties of the Fourier Transform
The FFT Algorithm
Some other Transforms
The Wavelet Transform
Digital Signal processors
Basic Architecture of a DSP Processor
Features of a Digital Signal Processor
Hardware Implementation of some basic DSP operations
Examples of practical DSP processors
Digital –Signal Processing Systems
Data Acquisition Systems
Telemetry
Pattern Recognition
Data Compression
Biometrics
Watermarking
Active Noise Control
Biography
Nadder Hamdy
