Title :
Stability of a neutral delay neuron system in the critical case
Author :
Xiaofeng Liao ; Nankun Mu
Author_Institution :
Coll. of Electron. & Inf. Eng., Southwest Univ., Chongqing, China
Abstract :
In this paper, the asymptotic stability properties of neutral-type neuron system are studied mainly in the critical case when the exponential stability is not possible. In the case of a critical value of the coefficient in neutral-type neuron system, the difficulty for our investigation is the fact that the spectrum of the linear operator is asymptotically approximated to the imaginary axis. Hence, based on the energy method, the asymptotic stability results for neutral-type neuron system are derived, and a complete analysis of the stability diagram is presented.
Keywords :
asymptotic stability; differential equations; neural nets; asymptotic stability properties; asymptotical approximation; critical case; critical value; energy method; imaginary axis; linear operator; neutral delay neuron system; neutral-type neuron system; stability diagram; Asymptotic stability; Delays; Differential equations; Equations; Mathematical model; Neurons; Stability analysis; asymptotic stability; critical case; neuron system; neutral-tyep;
Conference_Titel :
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6627-1
DOI :
10.1109/IJCNN.2014.6889612
