Structure optimization method of reserve pool network based on excitability and inhibition STDP

An optimization method and inhibitory technology, applied in the field of artificial neural network, can solve the problems of limited experience data, large subjective influence, and time-consuming, etc., to achieve large network information capacity, excellent network performance, and to achieve excitability and inhibition. The effect of sexual balance

Pending Publication Date: 2020-03-10
TIANJIN MEDICAL UNIV
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Problems solved by technology

[0003] The reserve pool module is a recurrent neural network. The neurons of the reserve pool network are connected randomly and sparsely. The connection weight has a decisive impact on the system performance. In the prior art, how to set the connection weight of the reserve pool network The value is mainly adjusted by experience, and it needs experienced people to complete it, and it

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  • Structure optimization method of reserve pool network based on excitability and inhibition STDP
  • Structure optimization method of reserve pool network based on excitability and inhibition STDP
  • Structure optimization method of reserve pool network based on excitability and inhibition STDP

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[0051] It should be noted that, in the case of no conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other.

[0052] The present invention will be described in detail below with reference to the accompanying drawings and examples.

[0053] The reserve pool module of the present invention adopts the Spiking Neural Network (SNN), which is constructed by simulating the structural features of the brain neuron network. Compared with the traditional artificial neural network model, it has the advantages of local learning and efficient calculation. In recent years, as a typical form of brain-inspired neural network (brain-inspired artificial intelligence), spiking neural network has received widespread attention and is called a new generation of neural network.

[0054] This application draws on the principles of neuroscience, and proposes an optimal design method for the neural network structure of the reserve pool based ...

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Abstract

The invention provides a structure optimization method of a reserve pool network based on excitability and inhibition STDP. The reserve pool network is a network formed by mutually connecting excitatory neurons E and inhibitory neurons I, the network has four connections: E-E, E-I, I-E and I-I, the connection weight of the E-E is adjusted through excitatory STDP, and the connection weight of the I-E is adjusted through inhibitory STDP. According to the invention, through an unsupervised learning rule of interaction between excitability STDP and inhibition STDP, excitability and inhibition balance is realized; a heterogeneous network structure which is consistent with the biological neural network in characteristics and has long-tail distribution characteristics is formed, the network information capacity is large, and the network performance is optimal.

Description

technical field [0001] The invention belongs to the technical field of artificial neural networks, in particular to a method for optimizing the structure of a reserve pool network based on excitatory and inhibitory STDP. Background technique [0002] Echo state networks (ESNs) are a new type of neural network model. The echo state network belongs to a multi-layer feedforward neural network model in terms of macroscopic structure. Its structure is as follows: figure 1 As shown, the local recurrent neural network in the middle part of the figure is the reservoir computing module, which belongs to the key part of the echo state network. [0003] The reserve pool module is a recurrent neural network. The neurons of the reserve pool network are connected randomly and sparsely. The connection weight has a decisive impact on the system performance. In the prior art, how to set the connection weight of the reserve pool network The value is mainly adjusted by experience, and it need...

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Application Information

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IPC IPC(8): G06N3/04G06N3/063G06N3/08
CPCG06N3/088G06N3/063G06N3/044
Inventor 王俊松姚洋
Owner TIANJIN MEDICAL UNIV
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