VLSI neural fuzzy classifier for handwriting recognition

Details VLSI neural fuzzy classifier for handwriting recognition VLSI neural fuzzy classifier for handwriting recognition

2006-12-05

2006-12-05

Mancuso, Joseph (Department: 2624)

Image analysis

Learning systems

Neural networks

C382S187000, C382S224000, C706S002000, C706S020000

Reexamination Certificate

active

07146037

ABSTRACT:
A handwriting recognition device using fuzzy logic and cellular neural network for unconstrained handwritten numeral classification is provided. The current mode VLSI classifier has a I/O circuit for inputting and outputting a plurality of membership functions. An extraction unit comprising a CCD extractor with a CNN structure and a compression unit receives a to-be-recognized character having a plurality of input features for generating a plurality of features values after compression. A membership function generator stores the plurality of membership functions and receives the plurality of features values to generate a plurality of current-type membership degrees. A plurality of switched-current integrators receives the plurality of current-type membership degrees for generating a plurality of synthesis membership degrees. A k-WTA circuit is provided for comparing the plurality of synthesis membership degrees and output the plurality of synthesis membership degrees as well as the corresponding characters in an order of magnitude.

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Li Guoxing, A modified Current Mode Hamming Neural Network for Totally Unconstrained Handwrittein Numeral Recognition, 1998, IEEE, 0-7803-4859-1, p. 1857-1960.
Jim Austin, “The Cellular Neural Network Associative Processor, C-NNAP”, May 1996, IEEE Monograph, p. 1-29.

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