Neural network information conversion method and system

A technology of information conversion and neural network, applied in the direction of biological neural network model, neural architecture, physical realization, etc., can solve the problems of different information and incompatibility between artificial neural network and spiking neural network

Active Publication Date: 2017-06-13
LYNXI TECH CO LTD
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Problems solved by technology

[0003] However, in traditional neuromorphic systems, there are mainly two forms of neural networks, one is spiking neural network and the other is artificial neural network. The two have different expressions for the same input information, resulting in artificial neural network and spiking Neural networks are not compatible due to the different information they process

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  • Neural network information conversion method and system
  • Neural network information conversion method and system
  • Neural network information conversion method and system

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Embodiment Construction

[0120] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0121] figure 1 It is a schematic flow chart of the neural network information conversion method of an embodiment, such as figure 1 The shown neural network information conversion methods include:

[0122] Step S1, receiving neuron input information from a previous neuron, including receiving artificial neuron input information from a previous artificial neuron, or receiving spike neuron input information from a previous spike neuron.

[0123] Specifically, in the neural network information conversion method provided in this embodiment, by identifying the input signals of different neural network...

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Abstract

The invention relates to a neural network information conversion method and system. The method comprises the steps that neuron input information input by a presynaptic neuron is received, wherein artificial neuron input information input by a presynaptic artificial neuron or spiking neuron input information input by the presynaptic spiking neuron is included; according to the artificial neuron input information input by the presynaptic artificial neuron, through a preset artificial information conversion algorithm, the artificial neuron input information is converted to spiking neuron conversion information; or according to the spiking neuron input information, through a preset spiking information conversion algorithm, the spiking neuron input information is converted to artificial neuron conversion information; the spiking neuron conversion information or the artificial neuron conversion information is output. According to the neural network information conversion method and system, in one neural network, two different neuron information modes are compatible, and the information processing ability of the neural network is improved.

Description

technical field [0001] The invention relates to the technical field of neural networks, in particular to a neural network information conversion method and system. Background technique [0002] Most of today's artificial neural network research is still implemented in von Neumann computer software and high-performance GPGPU (General Purpose Graphic Processing Units) platform. The hardware overhead, energy consumption and information of the whole process The processing speed is not optimistic. For this reason, the field of neuromorphic computing has developed rapidly in recent years, that is, using hardware circuits to directly construct neural networks to simulate the functions of the brain, trying to achieve a computing platform that is massively parallel, low-energy, and capable of supporting complex pattern learning. [0003] However, in the traditional neuromorphic system, there are two main forms of neural network, one is spiking neural network and the other is artific...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/063
CPCG06N3/04G06N3/063
Inventor 裴京吴臻志施路平邓磊
Owner LYNXI TECH CO LTD
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