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.
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[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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