1. A neural network comprising a plurality of sequential subnetworks, said plurality having at least a first subnetwork and a second subnetwork, wherein (A) said first subnetwork is configured to accept a plurality of input signals from sources external to said neural network and comprises: (1) a first plurality of patches, wherein (i) each patch of said plurality (a) responds to and records features of said input signals, (b) has a patch identifier and produces a similarity measure, said similarity measure having a value corresponding to a similarity between a feature recorded by said patch from a training pattern and a feature of an input signal, and (ii) said first plurality of patches generates first patch outputs, and (2) a first plurality of output neurons which accepts input from said first patch outputs and generates first neuron outputs; (B) said second subnetwork comprises a second plurality of patches and a second plurality of output neurons, wherein said second plurality of patches accepts said first neuron outputs as input and generates second patch outputs, and wherein said second plurality of output neurons accepts said second patch outputs as inputs and generates second neuron outputs; (C) all subnetworks of said plurality of sequential subnetworks, exclusive of said first subnetwork, are linked such that each subnetwork accepts as inputs neuron outputs of the immediately preceding subnetwork, and (D) inputs to the final subnetwork of said plurality of sequential subnetworks further include unconditioned stimuli.