An artificial neuron for use in a neural processing network comprises a plurality of input signal lines (1), an arrangement for computing a nonlinear function of the sum of the inputs (Xn) multiplied by associated weights (Wn), and a saturating delta-sigma modulator (8) which oversample the computed value and prdouces an encoded neuron output signal (U). Conversion of signals for use by these neurons preferably is performed by delta-sigma modulators (8) at the inputs to the neurons, which may be incorporated directly into sensors (71). Processing of the output signals from the neuron includes low-pass filtering and decimation (61). The present invention may be used in many diverse areas. For example, arrays of sensors (71) with delta-sigma modulators (8) 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.
ARTIFICIAL NEURONS USING DELTA-SIGMA MODULATION