Yujiao Huang

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This paper addresses the multistability problem of n-dimensional complex-valued recurrent neural networks with real-imaginary-type activation functions. Sufficient conditions are proposed for checking the existence of 1⁄2ð2aþ 1Þð2b þ 1Þ n ða; b P 1Þ equilibria. Under these conditions, 1⁄2ðaþ 1Þðb þ 1Þ n equilibria are locally exponentially stable and the(More)
In this paper, themultistability andmultiperiodicity issues are discussed for 2n-dimensional delayed bidirectional associative memory neural networks with r-level discontinuous activation functions. Sufficient conditions are established to ensure the existence of rn locally exponentially stable equilibria. As an extension of multistability, conditions are(More)
This paper is concerned with the dynamical stability analysis of multiple equilibrium points in recurrent neural networks with time-varying delays and discontinuous activation functions. Based on the decomposition of state space, some sufficient conditions for the existence of multiple equilibrium points are established, which ensure that n-dimensional(More)
This paper presents two new design procedures for synthesizing autoassociative memory and heteroassociative memory based on recurrent neural networks with different external inputs and mixed delays. Sufficient criteria are established to guarantee the global exponential stability for recurrent neural networks with mixed delays. The design procedures are(More)
Individual farmers represent the main management entities of agricultural production under the family-contract responsibility system in China, and thus play crucial roles in the prevention and control of agricultural nonpoint source (ANPS) pollution. The analysis of the farmers' perceptions of ANPS pollution as well as the factors affecting their(More)
This paper addresses the multistability problem of ndimensional memristive neural networks with a class of general nonmonotonic activation functions. Sufficient conditions are proposed for checking the existence of (2l+3) equilibria, of which (l+2) equilibria are locally exponentially stable. The obtained stability results improve and extend the existing(More)
The term Internet of Things is often used to talk about the trend of embedding microprocessors in everyday devices and connecting them to the Internet. The Internet of Things poses challenging communication requirements since the participating devices are heterogeneous, resource-constrained and operate in an ever changing environment. To cope with those(More)
The multistability problem is discussed for 2n-dimensional bidirectional associative memory (BAM) neural networks with a general class of activation functions. By using analysis approach and decomposition of state space, R<sup>2n</sup> can be divided into 3<sup>n</sup> regions. 2<sup>n</sup> regions of them are positive invariant, and under some conditions,(More)
This paper studies the multistability properties of linear threshold discrete-time recurrent neural networks. Based on local inhibition, conditions for boundedness are derived. Under these conditions, global attractive sets are established. By using decomposition of state space, it is shown that the n-neuron recurrent neural networks can have 2n local(More)