Effect of Learning Rate on the Recognition of Images

This paper presents a study for the effect of learning rate on an approach for texture classification anddetection based on the neural network principle. This neural network consists of three layers, which areinput, output, and hidden layers. The back propagation technique is considered. A computer algorithmis deduced and applied. In this work, the synthetic textures are generated. The results are taken for themodern computer of AT 486 type. The mathematical analysis is summarized in order to illustrate theeffect of learning rate parameter on the exact discrimination during processing. This effect is studiedthrough applications. The minimum consumed time for the computational time of classification inindustry is correlated to correspond only the use of only 2 units in the hidden layer of a neural networkfor real images instead of 11 units