We propose in this paper an extended model of the random neural networks, whose architecture is multi-feedback. In this case, we suppose different layers where the neurons have communication with the neurons of the neighbor layers. We present its learning algorithm and its possible utilizations; specifically, we test its use in an encryption mechanism where each layer is responsible of a part of the encryption or decryption process. The multilayer random neural network is a stochastic neural model, in this way the entire proposed encryption model has that feature.
['Jose Aguilar', 'Cristhian Molina']
The Multilayer Random Neural Network