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Hybrid computing system of artificial neural network and impulsive neural network

A pulse neural network and artificial neural network technology, applied in the field of neural network computing systems, can solve problems such as difficulty in description, discontinuity of neuron models, limitation of calculation scale and accuracy, and achieve the effect of ensuring accuracy

Active Publication Date: 2015-11-25
LYNXI TECH CO LTD
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the discontinuity of the neuron model of the spiking neural network, the complexity of space-time coding, and the uncertainty of the network structure make it difficult to describe the overall network mathematically, so it is difficult to construct an effective and general supervised learning algorithm. Limits its computational scale and accuracy

Method used

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  • Hybrid computing system of artificial neural network and impulsive neural network
  • Hybrid computing system of artificial neural network and impulsive neural network
  • Hybrid computing system of artificial neural network and impulsive neural network

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Embodiment Construction

[0032] The artificial neural network and pulse neural network hybrid computing system provided by the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0033] The first embodiment of the present invention provides a hybrid computing system 100 of artificial neural network and spiking neural network, including at least two basic computing units 110, at least one of which is an artificial neural network computing unit, In charge of artificial neural network calculations, at least one is a spiking neural network computing unit, responsible for spiking neural network computing, the at least two basic computing units 110 are connected to each other according to the topology, and jointly realize the neural network computing function.

[0034] See figure 1 , the at least one artificial neural network computing unit and the at least one impulse neural network computing unit can be regarded as an indepe...

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Abstract

Provided in the invention is a hybrid computing system of an artificial neural network and an impulsive neural network. The hybrid computing system comprises a plurality of neural network computing units; one part of the neural network computing units is an artificial neural network computing unit being responsible for artificial neural network computing; and the other parts of the neural network computing units are impulsive neural network computing units responsible for impulsive neural network computing. The multiple basic computing units are mutually connected according a certain topological structure, thereby realizing a neural network computing function jointly. According to the hybrid computing system, the computing modes of the two kinds of neural networks containing the artificial neural network and the impulsive neural network are combined to realize real-time multi-mode or complex space-time signal calculation rapidly and guarantee the computing precision.

Description

technical field [0001] The invention relates to a neural network computing system. Background technique [0002] A neural network is a computing system that imitates the synapse-neuron structure of a biological brain for data processing. It consists of multi-layered computing nodes and connections between layers. Each node simulates a neuron and performs a specific operation, such as an activation function. The connection between nodes simulates a synapse, and the weighted value of the connection to the input from the upper layer node represents the synaptic weight. Neural networks have powerful nonlinear and adaptive information processing capabilities. [0003] The neuron in the artificial neural network processes the accumulated value from the connection input with the activation function as its own output. Corresponding to different network topologies, neuron models and learning rules, artificial neural networks include dozens of network models such as perceptrons, Hop...

Claims

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Application Information

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IPC IPC(8): G06N3/04
Inventor 施路平裴京王栋邓磊李国齐
Owner LYNXI TECH CO LTD
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