A novel approach for implementation of adaptive learning rate neural networks

In this paper hardware implementation of adaptive learning rate neural networks is studied. Same design guidelines are presented to improve integration of learning algorithm into the hardware. By using them, it is possible to design more robust artificial neural networks which are capable of handling a learning algorithm in analog chips. According to the proposed technique, a design area for selecting the best hardware characteristic is obtained by performing evolutionary algorithms.