Abstract: An integrated circuit amplifier having a random input offset voltage is adaptable such that the input offset voltage may be cancelled out. An input node is a floating input node and is coupled to a source of input signal by a first capacitor. A second capacitor is connected between the output of the amplifier and the floating node. An ultraviolet window above the second capacitor allows the floating node to be charged, by the application of ultraviolet light, to a voltage which effectively cancels the input offset voltage.

Abstract: There is disclosed herein a method and apparatus for learning the characteristics of an event and for recognizing events which have been previously learned. The apparatus is comprised of forward and feedback matrices which process input signals characterizing events to be learned by comparing the convergence responses generated by the input signals at successively different levels of convergence threshold. The convergence threshold is altered until an acceptable range of convergence is reached, and then the pattern of convergence is learned. The pattern of convergence is stored for future reference. In recognition mode, the input signals are again processed at successively different convergence threshold levels until an acceptable range of convergence is reached. The pattern of convergence is then compared to the stored convergence patterns of known events to determine if the event is known.

Abstract: There is disclosed herein a recognize only embodiment of a recognition matrix comprised of a forward matrix and a reverse matrix each having a plurality of contacts which cause convergence responses on target lines when an input signal is received by said contact. Learning is performed by changing the characteristics of the contacts to alter the convergence responses they cause in accordance with a learning rule involving the comparison of total convergence response on each target line to a convergence threshold. The contacts are not programmed ad hoc in the field as events are individually learned. Instead each contact is programmed permanently by the user for a class of events which is fixed and which can never change. The user typically performs the learning on a computer simulator for all the events which a particular system is to be used to recognize.