Stability analysis OS discrete-time recurrently connected neural network
作者： Tianping Chen , Wen Lian Lu
DOI: 10.1109/ICONIP.2002.1202196
关键词:
摘要: In this paper, we discuss dynamics of the discrete-time recurrently asymmetrically connected neural networks (DTRACNN). We propose an effective approach to study global stability networks. give some sufficient conditions for (DRACNN) being exponentially stable. also a bound step size such that iteration converges. As consequence, derive exponential continuous-time (CTRACNN), i.e., systems are controlled by differential equations.
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