Feedback Nerual Network(一):Concept

本文介绍了Hopfield神经网络的基本概念,包括离散型和连续型Hopfield神经网络,并探讨了其稳定状态及工作模式,如异步模式和同步模式。

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It requires a certain period of working time, then can reach Stable Status, so it is a Dynamic Network、

 

 

 

Two types of Feedback NN according to the value of output is discrete or continuous
DHNN: Discrete Hopfield NN
CHNN: Continuous Hopfield NN

 

If system is stable, then it will converge from any initial state to a Stable State
If system is unstable, then the self-oscillation with limited amplitude or ultimate-loop 极限環 will be occurred, because of the output is 1 & -1 or 1 & 0 binary states.

 

Structure & Work Mode:

 


For each node of Discrete Hopfield neuron:it is similiar with feedforward network,unless a feedback input.

 

 

 

 

 

 Two Work Modes:
1Asynchronous Mode
Each time only one node of neurons adjusts his status, all the other nodes keep their status unchanged .

The order of adjustment can be selected dynamically or following a pre-setting order ( Here k stands for kth step ).

 

 2Synchronous Mode
All the nodes of neurons are adjusted simultaneously.

 

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