Related Experiment Videos
Multistability of recurrent neural networks with time-varying delays and the piecewise linear activation function
Zhigang Zeng1, Tingwen Huang, Wei Xing Zheng
1Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China. zgzeng@mail.hust.edu.cn
Abstract:
In this brief, stability of multiple equilibria of recurrent neural networks with time-varying delays and the piecewise linear activation function is studied. A sufficient condition is obtained to ensure that n-neuron recurrent neural networks can have (4k - 1)(n) equilibrium points and (2k)(n) of them are locally exponentially stable. This condition improves and extends the existing stability results in the literature. Simulation results are also discussed in one illustrative example.
Related Concept Videos
Classification of Systems-II
Piecewise-Defined Functions
Linear time-invariant Systems
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be calculated...
Multi-input and Multi-variable systems
In the absence of...
Types of Functions III
Linear Approximation in Frequency Domain
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.