Data processing device with network structure and its learning p

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395 24, G06F 1518

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052396185

ABSTRACT:
An output layer in a layered neural network uses a linear function or a designated region (linear region) of a threshold function instead of the threshold function to convert an input signal to an analog output signal When the basic unit uses the linear function, a limiter for limiting the output to a region between 1.0 and 0. When the basic unit uses the designated linear region of the threshold function, a limiter limits the output to a region between 0.8 and 0.2. Upon a learning operation, the error propagation coefficient is determined as a constant value such as 1/6 and when the majority of the desired values are 1 or near 1, an error value regarding the opposite desired value 0 is amplified, and when the output values become equal to or more than 1, it is deemed that there is no error with regard to the output of more than 1 in case of many outputs 1, thereby speeding up an operation of updating the weight.

REFERENCES:
McClelland et al., Explorations in Parallel Distributed Processing, MIT Press, 1988, pp. 1-3, 137-150.
Kung et al., "A Unified Systolic Architecture for Artificial Neural Networks", Jour. Parallel & Dist. Processing, Jun. 1989, pp 358-387.
Eberhardt et al., "Design of Parallel Hardware Neural Network Systems from Custom Analog VLSI `Building Block` Chips," ICNN, Jun. 1989, vol. 2, pp. II-183-II190.
Lippmann, R. P., "An Introduction to Computing with Neural Nets", IEEE ASSP Magazine, Apr. 1987, 4-22.
Patent Abstracts of Japan, vol. 13, No. 448 (p. 942), Oct. 9, 1989 for JP-A-173257.
Signal Processing IV: Theories and Applications, vol. 1, Sep. 1988, North Holland pp. 7-14, J. Herault.
European Search Report, The Hague, search completed Aug. 5, 1991.

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