초록 ▼

An artificial neuron for use in a neural processing network comprises a plurality of input signal lines, an arrangement for computing a nonlinear function of the sum of the inputs multiplied by associated weights, and a saturating delta-sigma modulator which oversamples the computed value and produc

An artificial neuron for use in a neural processing network comprises a plurality of input signal lines, an arrangement for computing a nonlinear function of the sum of the inputs multiplied by associated weights, and a saturating delta-sigma modulator which oversamples the computed value and produces an encoded neuron output signal. Conversion of signals for use by these neurons preferably is performed by delta-sigma modulators at the inputs to the neurons, which may be incorporated directly into sensors. Processing of the output signals from the neuron includes low-pass filtering and decimation. The present invention may be used in many diverse areas. For example, arrays of sensors with delta signal modulators may be coupled with a network of the neurons to form an intelligent vision system. Linear signal processing, both conventional and adaptive, can be done by a simple neuronal system that operates linearly.

대표청구항 ▼

A sensor for use in a neural network, comprising: a sensor for sensing a parameter and outputting an analog signal; an integrator coupled to said sensor, said integrator receiving the analog signal and outputting an integrated signal; a comparator receiving said integrated signal and comparing said

A sensor for use in a neural network, comprising: a sensor for sensing a parameter and outputting an analog signal; an integrator coupled to said sensor, said integrator receiving the analog signal and outputting an integrated signal; a comparator receiving said integrated signal and comparing said integrated signal with a reference value, and producing a two-state signal in response; a latch receiving said two-state signal, and providing an output signal to said neural network.