State Estimation for Neural Networks with Leakage Delay and Time-Varying Delays | Zendy

Jing Liang | Zendy; Zengshun Chen | Zendy; Qiankun Song | Zendy

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State Estimation for Neural Networks with Leakage Delay and Time-Varying Delays

Author(s) -

Jing Liang,

Zengshun Chen,

Qiankun Song

Publication year - 2013

Publication title -

abstract and applied analysis

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.228

H-Index - 56

eISSN - 1687-0409

pISSN - 1085-3375

DOI - 10.1155/2013/289526

Subject(s) - mathematics , control theory (sociology) , state (computer science) , artificial neural network , leakage (economics) , linear matrix inequality , matrix (chemical analysis) , state dependent , mathematical optimization , algorithm , computer science , control (management) , materials science , mathematical economics , artificial intelligence , machine learning , economics , composite material , macroeconomics

The state estimation problem is investigated for neural networks with leakage delay and time-varyingdelay as well as for general activation functions. By constructing appropriate Lyapunov-Krasovskii functionals andemploying matrix inequality techniques, a delay-dependent linear matrix inequalities (LMIs) condition is developedto estimate the neuron state with some observed output measurements such that the error-state system is globallyasymptotically stable. An example is given to show the effectiveness of the proposed criterion

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