1. A method for emulating a feed forward, segmented neural network having a large number of inputs, said method comprising the steps of: (a) modeling a segmented neural network having a large number of inputs as multiple network layers of subnetworks segmented such that each subnetwork within a network layer receives totally different inputs than all other subnetworks within said network layer, a plurality of said multiple network layers each having an even number of segmented subnetworks, each subnetwork comprising a plurality of interconnected sublayers, each sublayer having a plurality of processing nodes, and each subnetwork being sized for realization as a single binary memory device; (b) training the segmented neural network modeled in step (a) while requiring that input and output values of each network layer comprise binary signals; (c) mapping all possible input and corresponding output values of each subnetwork of said trained segmented neural network; (d) storing the mapped input and output values of each subnetwork in an associated binary memory device such that behavior of each subnetwork of the trained segmented neural network is emulated completely by the associated binary memory device; and (e) electrically interconnecting associated binary memory devices in a circuit arrangement corresponding to connection of the subnetworks in the modeled segmented neural network.