Applied Signal Processing Concepts, Circuits, and Systems

Providing a unified treatment of these related fields, Applied Signal Processing introduces underlying principles, basic concepts, designs, and implementation of signal processing techniques and systems. This book discusses basic analog and digital processing operations and filters, presenting a detailed description of interfacing devices between the analog and digital domains. The text also covers multi-rate signal processing applications, discrete-time transforms, and digital signal processing hardware. With illustrative examples, it also includes practical applications to fields such as forensics, biomedicine, remote sensing, active noise control, and pattern recognition.

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.  

Introduction 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