Multi-stable state oscillation circuit based on Hopfield nerve network

A neural network and oscillating circuit technology, applied in the field of multi-stable state oscillating circuits, can solve problems such as undiscovered multi-stable states, and achieve the effects of important biological significance and value, easy implementation, and simple model structure.

Inactive Publication Date: 2018-03-09
CHANGZHOU UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] So far, no such multi-stable states have been found in Hopfield-based neural networks

Method used

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  • Multi-stable state oscillation circuit based on Hopfield nerve network
  • Multi-stable state oscillation circuit based on Hopfield nerve network
  • Multi-stable state oscillation circuit based on Hopfield nerve network

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Embodiment Construction

[0020] Mathematical model: a kind of multi-stable state oscillation circuit based on Hopfield neural network of the present embodiment is as figure 1 shown. At first, the present invention is based on a kind of Hopfield neural network model of 3 neurons, and this mathematical model can be expressed as:

[0021]

[0022] in, is the neuron state vector, tanh(x)=[tanh(x 1 ), tanh(x 2 ), tanh(x 3 )] T is a neuron activation nonlinear function, W is a synaptic weight matrix, which can be expressed as

[0023]

[0024] Among them, k is the coupling connection weight of the first neuron to the third neuron.

[0025] The nonlinear system described by equation (1) is symmetric about the origin. Its symmetry can be obtained from (x 1 ,x 2 ,x 3 )→(–x 1 ,–x 2 ,–x 3 ) The invariance of the model after transformation is obtained, which means that if (x 1 ,x 2 ,x 3 ) is a solution of system (1), then (–x 1 ,–x 2 ,–x 3 ) is its other solution.

[0026] make is an ...

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Abstract

The invention discloses a multi-stable state oscillation circuit based on a Hopfield nerve network; the circuit comprises an operational amplifier, and a resistor and / or capacitor connected with the operational amplifier, thus finishing the adding, subtracting and integration operations of the nerve network; the circuit employs an existing commercial discrete components design, and develops a hardware circuit based on the Hopfield nerve network. The circuit can form multi-attractor coexistence behaviors under different original states, i.e., multi-stable states, thus providing important practical application values in the biology and information engineering fields.

Description

technical field [0001] The present invention relates to a multi-stable state oscillation circuit based on Hopfield neural network, which helps to deeply understand the role of this multi-stable state in brain information processing and cognitive functions, and provides neurodynamic insights for the understanding of brain functions. Explanation. Background technique [0002] Hopfield neural network is an important milestone in the history of neural network development. It has a wide range of applications in combination optimization pattern recognition, associative memory and stereo vision matching. When the neuron activation function adopts a nonlinear function, the Hopfield neural network system belongs to a nonlinear dynamic system. Like the traditional nonlinear dynamic system, it can also generate chaotic attractors and periodic limits within a certain parameter range. Complex nonlinear dynamic behaviors such as rings and stable point attractors illustrate that the Hopfi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/063G06N3/04H03K3/3568
CPCH03K3/3568G06N3/063G06N3/044
Inventor 徐权胡爱黄钱辉蒋涛宋哲孙梦霞
Owner CHANGZHOU UNIV
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