Learning process for neural network - comparing sample signals and categorising for use in backward learning process

摘要

The learning process is used with a neural network that has an input layer (1) of 7 frames together with a further two layers (2,3) and an output layer (4). Each data element has a time period of 70 ms. In a first operation a learning sample is selected and the differences to other samples is determined in a second operation. Samples are categorised and the weightings determined. When all values are obtd. a backward learning algorithm is executed to improve the results. USE/ADVANTAGE - For phoneme comparison in speech recognition system. Improves the learning rate of the network.