Overview
- Authors:
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R. Tolimieri
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Center for Large Scale Computing, City University of New York, New York, USA
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Myoung An
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Center for Large Scale Computing, City University of New York, New York, USA
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Chao Lu
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Center for Large Scale Computing, City University of New York, New York, USA
- Editors:
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C. S. Burrus
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Department of Electrical and Computer Engineering, Rice University, Houston, USA
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Table of contents (15 chapters)
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- R. Tolimieri, Myoung An, Chao Lu
Pages 1-35
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- R. Tolimieri, Myoung An, Chao Lu
Pages 36-71
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- R. Tolimieri, Myoung An, Chao Lu
Pages 72-93
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- R. Tolimieri, Myoung An, Chao Lu
Pages 94-118
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- R. Tolimieri, Myoung An, Chao Lu
Pages 119-131
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- R. Tolimieri, Myoung An, Chao Lu
Pages 132-175
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- R. Tolimieri, Myoung An, Chao Lu
Pages 176-186
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- R. Tolimieri, Myoung An, Chao Lu
Pages 187-197
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- R. Tolimieri, Myoung An, Chao Lu
Pages 198-221
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- R. Tolimieri, Myoung An, Chao Lu
Pages 222-245
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- R. Tolimieri, Myoung An, Chao Lu
Pages 246-261
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- R. Tolimieri, Myoung An, Chao Lu
Pages 262-279
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- R. Tolimieri, Myoung An, Chao Lu
Pages 280-294
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- R. Tolimieri, Myoung An, Chao Lu
Pages 295-321
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- R. Tolimieri, Myoung An, Chao Lu
Pages 322-347
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Back Matter
Pages 348-350
About this book
This book is based on several courses taught during the last five years at the City College of the City University of New York and at Fudan University, Shanghai, China in the Summer, 1986. It was originally our intention to present to a mixed audience of electrical engineers, mathematicians and computer scientists at the graduate level, a collection of algorithms which would serve to represent the vast array of algorithms designed over the last twenty years for com puting the finite Fourier transform (FFT) and finite convolution. However, it was soon apparent that the scope of the course had to be greatly expanded. For researchers interested in the design of new algorithms, a deeper understanding of the basic mathematical con cepts underlying algorithm design was essential. At the same time, a large gap remained between the statement of an algorithm and the implementation of the algorithm. The main goal of this text is to describe tools which can serve both of these needs. In fact, it is our belief that certain mathematical ideas provide a natural lan guage and culture for understanding, unifying and implementing a wide range of digital signal processing (DSP) algorithms. This belief is reenforced by the complex and time-consumming effort required to write code for recently available parallel and vector machines. A significant part of this text is devoted to establishing rules and precedures which reduce and at times automate this task. In Chapter 1, a survey is given of basic algebra.
Authors, Editors and Affiliations