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Content Provider | IEEE Xplore Digital Library |
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Author | Kyungtae Han Olson, A.G. Evans, L. |
Copyright Year | 2006 |
Description | Author affiliation: Dept. of Electr. & Comput. Eng., Univ. of Texas at Austin, Austin, TX (Kyungtae Han; Olson, A.G.; Evans, L.) |
Abstract | Many digital signal processing and communication algorithms are first simulated using floating-point arithmetic and later transformed into fixed-point arithmetic to reduce implementation complexity. For the floating-point to fixed-point transformation, this paper describes two methods within an automated transformation environment. The first method, a gradient-based search for single-objective optimization with sensitivity information, provides a single solution, and can become trapped in local optima. The second method, a genetic algorithm for multi-objective optimization, provides a family of solutions that form a tradeoff curve for signal quality vs. implementation complexity. We provide case studies for an infinite impulse response filter. In the case study, implementation complexity is lookup table area for a field programmable gate array (FPGA) realization. We have made the transformation methods available in a software release on the Web. |
Starting Page | 79 |
Ending Page | 83 |
File Size | 295349 |
Page Count | 5 |
File Format | |
ISBN | 1424407842 |
ISSN | 10586393 |
DOI | 10.1109/ACSSC.2006.356588 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2006-10-29 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Signal processing algorithms Digital signal processing Hardware Finite impulse response filter Floating-point arithmetic Optimization methods Genetic algorithms Field programmable gate arrays Fixed-point arithmetic Distortion measurement |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Computer Networks and Communications |
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