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Making signal processing real--out of the lab and down to the street. Moving technology from ideal research conditions into real-life applications is always a challenge. The computing and timing issues involved in signal processing make it an especially difficult transition. Real-Time Signal Processing covers the entire process of implementing signal processing algorithms, from real-time concepts to multiprocessors and tradeoff analyses, and it provides a toolkit of hardware and software computing elements. This book walks through the entire system design process, from requirements development through life-cycle systems engineering, project management, integration, testing, and maintenance.
To work within the limitations of functioning implementations, Real-Time Signal Processing describes techniques that can be used across a broad range of hardware and software systems. Special emphasis is given to:
- Differences between hardware and software realization.
- Tradeoffs of space against time for both software and hardware.
- Off-the-shelf vs. custom implementations.
The book provides a process for mapping algorithms and architectures and illuminates it with several examples, including:
- Wavelet analysis.
- Linear predictive coding.
- Compression of speech and images.
- Recognition of speech and images.
- Hidden Markov modeling.
- Image formation for synthetic aperture radar.
When it's time to put theory into practice, Real-Time Signal Processing provides the complete roadmap. --This text refers to an out of print or unavailable edition of this title.
1. Real Time Concepts. Definition of Real Time. Structural Levels of Processing. Approximate Processing. 2. Processors. Definition of Processor. General Purpose Microprocessor. Digital Signal Processor. Specialized Processors. 3. Tradeoff Analysis. Trade Study. Algorithm Complexity. Software-Hardware Tradeoffs. 4. Space-Time Tradeoffs. Space-Time Tradeoffs in Software. Space-Time Tradeoffs in Hardware. 5. Algorithm-Architecture Mapping: Principles. Introduction. Processes and Procedures. Tools and Techniques. 6. Algorithm-Architecture Mapping: Examples. Basic Descriptions of Architecture and Algorithm. Two-Dimensional Convolution on One Processor. Two-Dimensional Convolution on Multiple Processors. Linear Prediction Coding Applied to Telephone Speech. Two-Dimensional Filter Mapped onto Multiple Processors. Synthetic Aperture Radar Image Formation. 7. Basic Hardware and Software Computing Elements. Introduction. Basic Components. 8. Components for Signal Analysis. Background. Fourier Transform. Wavelet Transform. Linear Predictive Coding. 9. Components for Signal Compression. Speech Coding. Vector Quantization. Image Compression. 10. Components for Signal Comparison. Real Time Pattern Comparison. Speech Recognition. Image Recognition. 11. System Design Methods and Tools. Design Processes. System Engineering. Requirements Design. Hardware Design. Software Design. System Integration and Testing. Example System Design. Index. About the Author
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