Abstract: Based on the encoding of deterministic finite-state automata (DFA) in discrete-time, second-order recurrent neural networks, an algorithm constructs an augmented recurrent neural network that encodes a FFA and recognizes a given fuzzy regular language with arbitrary accuracy.

Abstract: A crosspoint (X-Y) matrix array of electrically reprogrammable memory logic elements, such as an array of dual dielectric insulated gate field effect transistor (IGFET) structures, is interconnected in a single electrically reprogrammable diode logic array circuit, both for computing the logic function(s) of many variables and for writing and erasing the function(s). Each logic element's high current path is in series with a separate unidirectional diode in order to prevent sneak paths. Electrical access circuitry is also provided for computing the logic function(s) of many variables, each funtion being electrically alterable.