| 摘要 |
PURPOSE:To realize the optimum filter in a short time by dividing a training pattern into plural partial patterns whose respective part can hold the statistical property of the whole patterns, and repeating learning. CONSTITUTION:A spatial filter is comprised of multilayer perceptrons 6, and a training control part 3 performs sequential learning by using one of partial learning pattern images after dividing an image for training into partial sets whose statistical property included in an original image can be prevented from being missed. Training is performed with the same partial learning pattern image when the error of the output image of the filter goes less than the error at the training last time and a value decided in advance, and a leaning pattern image is replaced by the next partial learning pattern image when the errors are different from each other, then, the learning for all the partial learning pattern images are repeated until the error of the output image goes less than the value decided in advance. Therefore, waste in the training is eliminated, and a remarkably effective filter quickly is realized. |
