A New Robust Training Law for Dynamic Neural Networks with External Disturbance: An LMI Approach
نویسندگان
چکیده
A new robust training law, which is called an input/output-to-state stable training law IOSSTL , is proposed for dynamic neural networks with external disturbance. Based on linear matrix inequality LMI formulation, the IOSSTL is presented to not only guarantee exponential stability but also reduce the effect of an external disturbance. It is shown that the IOSSTL can be obtained by solving the LMI, which can be easily facilitated by using some standard numerical packages. Numerical examples are presented to demonstrate the validity of the proposed IOSSTL.
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تاریخ انتشار 2011