why there is no self-connection for the feedback in Hopfiled network? what is the advantages ?
why there is no self-connection for the feedback in Hopfiled network? what is the advantages ?
Homework Answers
In case of the continuous version of the Hopfield neural network, we have to consider neural self-connections wij≠0 and choose as an activation function a sigmoid function. With these new adjustments, the training algorithm operates in the same way.
The convergence property of Hopfield’s network depends on the structure of W (the matrix with elements wij) and the updating mode. An important property of the Hopfield model is that if it operates in a sequential mode and W is symmetric with nonnegative diagonal elements, then the energy function
(7.71)Ehs(t)=12∑i=1n∑j=1nwijxi(t)xj(t)-∑i=1nbixi(t)=-12xT(t)Wx(t)-bTx(t)
is nonincreasing [138]. The network always converges to a fixed point.
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why there is no self-connection for the feedback in Hopfiled
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