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IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 4
A Programmable Neural-Fuzzy Processor for Handwritten Digit Classification
Como, Italy
July 24-July 27
ISBN: 0-7695-0619-4
Guoxing Li, Tsinghua University
Bingxue Shi, Tsinghua University
A novel current-mode processor based on single layer Perceptron and fuzzy logic for handwritten digit classification is put forward in this paper. This processor can be reconfigured as Perceptron based classifier or fuzzy logic based classifier, it benefits from the fact that there is a similar architecture between single Perceptron and SUM-MAX based fuzzy logic when they are used as a classifier. Both of them share the 11x10 PE (Processing Element) array, WTA (Winner-Take-All) network, switched current integrators and I/O ports. It can give 11 binary final classifying results, of which one is regarded as rejecting signal, after the feature vector with length variability is fed into the PE array. This processor has been implemented with double metals, single poly 1.2um CMOS technology.
Citation:
Guoxing Li, Bingxue Shi, "A Programmable Neural-Fuzzy Processor for Handwritten Digit Classification," ijcnn, vol. 4, pp.4057, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 4, 2000
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