Abstract: The neural engine (20) is a hardware implementation of a neural network for use in real-time systems. The neural engine (20) includes a control circuit (26) and one or more multiply/accumulate circuits (28). Each multiply/accumulate circuit (28) includes a parallel/serial arrangement of multiple multiplier/accumulators (84) interconnected with weight storage elements (80) to yield multiple neural weightings and sums in a single clock cycle. A neural processing language is used to program the neural engine (20) through a conventional host personal computer (22). The parallel processing permits very high processing speeds to permit real-time pattern classification capability.

Abstract: A neural network signal processor (NSP) (20) that can accept, as input, unprocessed signals (32), such as those directly from a sensor. Consecutive portions of the input waveform are directed simultaneously to input processing units, or "neurons" (22). Each portion of the input waveform (32) advances through the input neurons (22) until each neuron receives the entire waveform (32). During a training procedure, the NSP 20 receives a training waveform (30) and connective weights, or "synapses" (28) between the neurons are adjusted until a desired output is produced. The NSP (20) is trained to produce a single response while each portion of the input waveform is received by the input neurons (22). Once trained, when an unknown waveform (32) is received by the NSP (20), it will respond with the desired output when the unknown waveform (32) contains some form of the training waveform (30).