Fast Algorithms for Signal Processing available in Hardcover
- Pub. Date:
- Cambridge University Press
Efficient signal processing algorithms are important for embedded and power-limited applications since, by reducing the number of computations, power consumption can be reduced significantly. Similarly, efficient algorithms are also critical to very large scale applications such as video processing and four-dimensional medical imaging. This self-contained guide, the only one of its kind, enables engineers to find the optimum fast algorithm for a specific application. It presents a broad range of computationally-efficient algorithms, describes their structure and implementation, and compares their relative strengths for given problems. All the necessary background mathematics is included and theorems are rigorously proved, so all the information needed to learn and apply the techniques is provided in one convenient guide. With this practical reference, researchers and practitioners in electrical engineering, applied mathematics, and computer science can reduce power dissipation for low-end applications of signal processing, and extend the reach of high-end applications.
|Publisher:||Cambridge University Press|
|Product dimensions:||7.00(w) x 9.80(h) x 1.00(d)|
About the Author
Richard E. Blahut is a Professor of Electrical and Computer Engineering at the University of Illinois, Urbana-Champaign. He is Life Fellow of the IEEE and the recipient of many awards including the IEEE Alexander Graham Bell Medal (1998) and Claude E. Shannon Award (2005), the Tau Beta Pi Daniel C. Drucker Eminent Faculty Award, and the IEEE Millennium Medal. He was named a Fellow of the IBM Corporation where he worked for over 30 years in 1980, and was elected to the National Academy of Engineering in 1990.
Table of Contents
1. Introduction; 2. Introduction to abstract algebra; 3. Fast algorithms for the discrete Fourier transform; 4. Fast algorithms based on doubling strategies; 5. Fast algorithms for short convolutions; 6. Architecture of filters and transforms; 7. Fast algorithms for solving Toeplitz systems; 8. Fast algorithms for trellis search; 9. Numbers and fields; 10. Computation in finite fields and rings; 11. Fast algorithms and multidimensional convolutions; 12. Fast algorithms and multidimensional transforms; Appendices: A. A collection of cyclic convolution algorithms; B. A collection of Winograd small FFT algorithms.