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First International Conference on Innovative Computing, Information and Control - Volume II (ICICIC'06)
The Hardware Implementation of A Multi-resolution Combined Fuzzy Min-Max Classifier Chip
Beijing, China
August 30-September 01
ISBN: 0-7695-2616-0
Y. Liang, Tsinghua University, China
S. Q. Fan, Tsinghua University, China
D. M. Jin, Tsinghua University, China
This paper presents the design and implementation of a multi-resolution combined fuzzy neural network classifier. To improve classification speed, a parallel structure is developed for the classifier. The classifier presented consists of 4 parallel classification logic units, each of which has the same structure and functions, so that the classification logic units can operate classification simultaneously and obtain results at the same time. The classifier is realized using field programmable gate array (FPGA) and application specific integrated circuit (ASIC). Test results show that the maximal operation frequency is 100MHz and the chip can be cascaded to achieve high speed classification.
Citation:
Y. Liang, S. Q. Fan, D. M. Jin, "The Hardware Implementation of A Multi-resolution Combined Fuzzy Min-Max Classifier Chip," icicic, vol. 2, pp.30-33, First International Conference on Innovative Computing, Information and Control - Volume II (ICICIC'06), 2006
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