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Global Exponential Stability of Bidirectional Associative Memory Neural Networks With Time Delays
2008
IEEE Transactions on Neural Networks
In this paper, we consider delayed bidirectional associative memory (BAM) neural networks (NNs) with Lipschitz continuous activation functions. By applying Young's inequality and Hölder's inequality techniques together with the properties of monotonic continuous functions, global exponential stability criteria are established for BAM NNs with time delays. This is done through the use of a new Lyapunov functional and an -matrix. The results obtained in this paper extend and improve previous
doi:10.1109/tnn.2007.908633
pmid:18334360
fatcat:agxf6vrtwrc3rkqc4f66z53dbm