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The Dahlquist Constant Approach to Stability Analysis of the Static Neural Networks

机译:静态神经网络稳定性的Dahlquist常数法

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摘要

Avoiding the difficulty of constructing a proper Lyapunov function, the generalized Dahlquist constant approach is employed to investigate the exponential stability of the static neural networks. Without assuming the boundedness, monotonicity of the activations, a new sufficient conditions for existence of an unique equilibrium and the exponential stability of the neural networks are presented. An example is given to show the effectiveness of our results.
机译:为避免构造适当的Lyapunov函数的困难,采用广义的Dahlquist常数方法来研究静态神经网络的指数稳定性。在不假设激活的有界性,单调性的情况下,提出了一个新的充分条件,用于存在唯一平衡和神经网络的指数稳定性。举例说明了我们的结果的有效性。

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