Finite-Time Recursive Neural Network for Quadratic Minimization Problems

doi:10.13438/j.cnki.jdzk.2019.02.006

Abstract

Abstract:

A recursive neural network model is utilized for solving the quadratic minimization problem,and a sign-bi-power activation function is added to the network model,which speeds up the convergence of the recursive neural network even to reach the finite-time convergence.Moreover,by adjusting the value of the designing parameter λ,the convergence performance of the recursive neural network can be further improved.Finally,the MATLAB is used to simulate and verify the recursive neural network model,and the numerical simulation results verify the effectiveness and superiority of the proposed finite-time recursive neural network model for solving the quadratic minimization problem.

Key words: quadratic minimization problem, finite-time convergence, recurrent neural network

ZHANG Yongsheng,XIAO Lin. Finite-Time Recursive Neural Network for Quadratic Minimization Problems[J]. Journal of Jishou University（Natural Sciences Edition), DOI: 10.13438/j.cnki.jdzk.2019.02.006.

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