| 摘要 |
PROBLEM TO BE SOLVED: To suppress drop to a local minimum and to execute a stable learning operation with less errors by correcting a connection weight parameter in a direction where the errors are reduced the most, while a learning coefficient is adjusted so as not to increase the errors, from a stage where the errors are reduced to the value of not more than a reference value. SOLUTION: A neural network initialization part 7 constitutes a neural network from the parameter of the number of elements or the like, initializes connection weight by random numbers and sets a neuro gain parameterβand the learning coefficientη. Then, aβvalue deciding part 9 decides the value of the neuro gain parameterβ. When all time sequential data are inputted, a steepest drop direction calculation part 11 calculates the steepest drop direction. Aηvalue deciding part 10 decides the value of the learning coefficientηand a connection weight matrix correction part 12 corrects connection weight, based on the decided learning coefficientηand the steepest drop direction.
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