The paper presents the concept of an autonomous hardware – a neuroprocessor, on which both neural networks with simple neurons used in information technologies and a biomorphic neural network can be based for modeling the work of the cortical column of the human brain. Neuroprocessor as a computational device of matrix-vector operations includes logical and memory matrices based on a combined memristor-diode crossbar. We present a functional diagram of a neuroprocessor, electrical circuits of a storage matrix and a universal logical matrix. The latter as a programmable logical matrix performs matrix-vector multiplication by successive conjunctions with inversion; as a switch directs the output pulses of neurons to the synapses of other neurons; as part of the input device of the neuroprocessor implements the primary processing of the signal in the digital mode by multiplying the matrix by a vector, converting the input data into the desired format; as part of the output device, compresses the information with the same multiplication for transmission to the interface unit. SPICE-simulation of the main nodes of the neuroprocessor showed high energy efficiency of the proposed matrices.


Разработка: студия Green Art