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In this letter, we investigate the stationary solutions of multiple output levels RTD-based cellular neural networks (CNN) by using Chua's driving-point plot methods. Moreover, we present some sufficient conditions, that are concise and easy to be validated, to determine the existence of the stationary solutions. Finally, we give four illustrative examples to show the effectiveness of our results.

In this paper, memory patterns of bidirectional associative memory (BAM) neural networks with time-delay are investigated based on stability theory. Several sufficient conditions are obtained such that the equilibrium point is locally exponentially stable when the point is located at the designated position. These conditions, which can be directly derived from the synaptic connection weights and the external input of the BAM neural networks, are very easy to be verified. In addition, three examples are given to show the effectiveness of the results.

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