| 摘要 |
PROBLEM TO BE SOLVED: To easily find out an optimum value without requiring much labor even when a user has no experience of a neural network by calculating a feature value from an information signal such as an image, sound and vibration in order to conduct product inspection and fault diagnosis, grasping the feature value as normal distribution and learning the neural network. SOLUTION: In a learning signal storing part, a pattern boundary setter prepares a boundary signal around an initial learning input signal belonging to the same category on the basis of an initial learning signal written in an initial learning input signal memory and writes the prepared boundary signal in a learning input signal memory together with the initial learning input signal. The pattern boundary setter prepares a boundary pattern of normal distribution around plural learning input patterns belonging to the same category by using the neural network. The boundary pattern obtained by calculating a mean value and a standard deviation from plural learning input patterns belonging to the same category and changing a part or all of the learning input patterns to a value obtained by adding or subtracting the real number times of the standard deviation to/from the mean value is used. |
