Multistability of periodic delayed recurrent neural network with memristors

作者：Bao Gang^*; Zeng Zhigang

来源：Neural Computing & Applications, 2013, 23(7-8): 1963-1967.

DOI：10.1007/s00521-012-0954-x

• Neural Network
• Memristor
• Periodic
• Limit cycle

This paper discusses the recurrent neural network (RNN) with memristors as connection weights. Memristor is a nonlinear resistor. Memristance varies periodically with time when the sinusoidal voltage source is applied. According to this property of memristor, it shows that coefficients of RNN with memristors are periodic functions with respect to time t. By dividing the state space and using contraction mapping theorem, one sufficient condition is obtained for multiperiodicity. And the periodic orbits located in saturation regions are locally exponentially stable limit cycles. At last, one example is given for verifying the validity of our result.

• 出版日期2013-12
• 单位华中科技大学