Author
Haijun Jiang
Bio: Haijun Jiang is an academic researcher from Xinjiang University. The author has contributed to research in topics: Synchronization (computer science) & Artificial neural network. The author has an hindex of 40, co-authored 227 publications receiving 4942 citations.
Papers published on a yearly basis
Papers
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TL;DR: It is shown by theoretic proof that the estimation bound of the settling time given in this paper is less conservative and more accurate compared with the classical results.
270 citations
TL;DR: The fact that there is no constant equilibrium point other than the origin for the reaction-diffusion neural networks with Dirichlet boundary conditions under the impulsive control is pointed out.
Abstract: This paper discuss the global exponential stability and synchronization of the delayed reaction-diffusion neural networks with Dirichlet boundary conditions under the impulsive control in terms of p-norm and point out the fact that there is no constant equilibrium point other than the origin for the reaction-diffusion neural networks with Dirichlet boundary conditions. Some new and useful conditions dependent on the diffusion coefficients are obtained to guarantee the global exponential stability and synchronization of the addressed neural networks under the impulsive controllers we assumed. Finally, some numerical examples are given to demonstrate the effectiveness of the proposed control methods.
215 citations
TL;DR: A sufficient condition in the sense of Caputo's fractional derivation to ensure the monotonicity of the continuous and differential functions and a new fractional-order differential inequality are derived, which play central roles in the investigation of the fractional adaptive control.
187 citations
TL;DR: Several new sufficient conditions ensuring the finite-time synchronization of memristor-based chaotic neural networks are obtained by using analysis technique, finite time stability theorem and adding a suitable feedback controller.
180 citations
TL;DR: In this article, the existence and α -exponential stability of the equilibrium point of fractional-order neural networks is investigated. But the authors only considered fractional order neural networks and did not consider fractional chaotic networks.
145 citations
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Journal Article•
28,685 citations
01 Jan 2015
3,828 citations
2,084 citations
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TL;DR: “Multivalued Analysis” is the theory of set-valued maps (called multifonctions) and has important applications in many different areas and there is no doubt that a modern treatise on “Nonlinear functional analysis” can not afford the luxury of ignoring multivalued analysis.
Abstract: “Multivalued Analysis” is the theory of set-valued maps (called multifonctions) and has important applications in many different areas. Multivalued analysis is a remarkable mixture of many different parts of mathematics such as point-set topology, measure theory and nonlinear functional analysis. It is also closely related to “Nonsmooth Analysis” (Chapter 5) and in fact one of the main motivations behind the development of the theory, was in order to provide necessary analytical tools for the study of problems in nonsmooth analysis. It is not a coincidence that the development of the two fields coincide chronologically and follow parallel paths. Today multivalued analysis is a mature mathematical field with its own methods, techniques and applications that range from social and economic sciences to biological sciences and engineering. There is no doubt that a modern treatise on “Nonlinear Functional Analysis” can not afford the luxury of ignoring multivalued analysis. The omission of the theory of multifunctions will drastically limit the possible applications.
996 citations