VLSI neural fuzzy classifier for handwriting recognition
First Claim
1. A handwritten numeral classifier using fuzzy logic and cellular neural network, comprising:
- an extraction unit using cellular neural network for receiving a scanned image having a plurality of input features, and compressing the received data of the scanned image to generate a plurality of feature values;
a membership function generator using fuzzy logic for storing a plurality of membership functions and receiving the feature values to generate a plurality of synthesis membership function degrees for the plurality of input features;
a k-WTA circuit for receiving the plurality of synthesis membership function degrees from the membership function generator and outputting the synthesis membership degrees in order of magnitude;
an I/O circuit for inputting programming codes to the membership function generator through off-chip memory units and receiving the synthesis membership degrees from the k-WTA circuit to output a final recognizing result of the scanned image; and
a clock generator and logic controller for generating clock cycle and control logic signals for controlling timing of and logic for operations of the extraction unit, membership function generator, and the k-WTA circuit.
1 Assignment
0 Petitions
Accused Products
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.
48 Citations
9 Claims
-
1. A handwritten numeral classifier using fuzzy logic and cellular neural network, comprising:
-
an extraction unit using cellular neural network for receiving a scanned image having a plurality of input features, and compressing the received data of the scanned image to generate a plurality of feature values;
a membership function generator using fuzzy logic for storing a plurality of membership functions and receiving the feature values to generate a plurality of synthesis membership function degrees for the plurality of input features;
a k-WTA circuit for receiving the plurality of synthesis membership function degrees from the membership function generator and outputting the synthesis membership degrees in order of magnitude;
an I/O circuit for inputting programming codes to the membership function generator through off-chip memory units and receiving the synthesis membership degrees from the k-WTA circuit to output a final recognizing result of the scanned image; and
a clock generator and logic controller for generating clock cycle and control logic signals for controlling timing of and logic for operations of the extraction unit, membership function generator, and the k-WTA circuit. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
-
Specification