Information processing apparatus and method

Data processing: artificial intelligence – Neural network – Structure

Reexamination Certificate

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Details

C706S012000, C706S014000, C706S015000, C706S016000

Reexamination Certificate

active

07324980

ABSTRACT:
This invention relates to an information processing device and method that enable generation of an unlearned new pattern. Data xtcorresponding to a predetermined time series pattern is inputted to an input layer (11) of a recurrent neural network (1), and a prediction value x*t+1is acquired from an output layer13. A difference between teacher data xt+1and the prediction value x*t+1is learned by a back propagation method, and a weighting coefficient of an intermediate layer12is set at a predetermined value. After the recurrent neural network is caused to learn plural time series patterns, a parameter having a different value from the value in learning is inputted to parametric bias nodes (11-2), and an unlearned time series pattern corresponding to the parameter is generated from the output layer (13). This invention can be applied to a robot.

REFERENCES:
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patent: 5956702 (1999-09-01), Matsuoka et al.
patent: 6249781 (2001-06-01), Sutton
patent: 6728691 (2004-04-01), Neuneier et al.
patent: 6735580 (2004-05-01), Li et al.
patent: 2002-86378 (2002-03-01), None
Takase, H. et al., “Time Sequential Pattern Transformation and Attractors of Recurrent Neural Networks”, In: Proc. of 1993 International Joint Conference on Neural Networks, 1993, pp. 2319-2321.

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