A neuron hardware device and a method for simulating a spiking neural network using the device

A technology of spiking neural network and hardware device, applied in biological neural network model, neural architecture, physical implementation, etc., can solve problems such as poor scalability, large simulation time, short development cycle, etc.

Inactive Publication Date: 2018-02-16
GUANGXI NORMAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Software modeling and simulating spiking neural networks are relatively easy to implement and have a short development cycle, but software is generally based on von Neumann’s serial execution architecture, so for large-scale neural networks, software simulation requires a lot of simulation time and can be poor scalability

Method used

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  • A neuron hardware device and a method for simulating a spiking neural network using the device
  • A neuron hardware device and a method for simulating a spiking neural network using the device
  • A neuron hardware device and a method for simulating a spiking neural network using the device

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Embodiment

[0043] see figure 1 , a neuron hardware device, comprising a neural network, the neural network comprising a plurality of neuron layers, the neuron layer comprising a plurality of neurons, the neurons comprising a synapse layer, the synapse layer comprising Multiple synapses.

[0044] see image 3 , the synapse is an IP core, and the input and output signal ports of the IP core include a pulse input port, a configuration information input port, a resource share input / output port in a recovery state, and a resource share input in an active state / output port, resource shares inactive state input / output port, synaptic current input / output port, synaptic efficiency utilization input / output port, and input / output handshake signal port.

[0045] The synaptic layer is a synaptic network formed by multiple synaptic connections in parallel.

[0046] see Figure 5 , the neuron includes a neuron computing core, a data packet decoder, a parameter memory, a pulse buffer, a cell contro...

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Abstract

The invention discloses a neuron hardware structure and a method for simulating a pulse neural network using the structure. The neuron hardware structure is characterized in that it includes a neural network, and the neural network includes a plurality of neuron layers. The neuron layer comprises a plurality of neurons, and the neuron comprises a synaptic layer, and the synaptic layer comprises a plurality of synapses; the method for simulating the pulse neural network with the above-mentioned neuron hardware structure is characterized in that it comprises the following Steps: 1) Determine the synapse model; 2) Simulate the synapse; 3) Simulate the neuron; 4) Simulate the neuron layer; 5) Simulate the neural network. This neuron hardware structure can reduce the hardware resources occupied by a single neuron node. By using this neuron hardware structure to simulate the spiking neural network, the simulation time is short, the scalability is good, and the hardware resources occupied by the spiking neural network can be reduced, thereby improving the ability of hardware devices to accommodate neurons.

Description

technical field [0001] The invention relates to a large-scale pulse neural network technology, in particular to a method for simulating a pulse neural network with a neuron hardware device. Background technique [0002] The rapid development of neuroscience has accumulated a lot of knowledge about the structure and function of the human brain. Studies have shown that the brain is composed of dense, complex interconnections of neurons, which exhibit many amazing properties, such as pattern recognition and decision-making control. The current understanding of biological neurons is that they transmit information and perform computations through the timing of spikes. The researchers proposed a computational model of spiking neural networks, which simulates behaviors such as information transmission between neurons and signal processing within neurons. At present, there are many fields using computing methods based on spiking neural networks, such as prediction, image processin...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/063G06N3/04
CPCG06N3/065G06N3/045
Inventor 罗玉玲万雷丘森辉莫家玲岑明灿刘俊秀
Owner GUANGXI NORMAL UNIV
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