Blind detection algorithm based on composite sinusoidal chaotic neural network
Liu Huan, Shujuan Yu, Yun Zhang, Rong Hu · 2014
For the phenomenon of premature occurred in the course of evolution of Hopfield neural network(HNN) and the slow convergence speed of Transient chaotic neural network(TCNN), a new blind detection algorithm based on composite sinusoidal chaotic neural network(CSCNN) is proposed in this paper. The presented algorithm experiences the process of coarse search based on chaos to fine search based on gradient dynamics characteristics and it can solve the blind detection of BPSK signal successfully taking advantages of the ergodic and stochastic characteristics of chaos. The simulation shows that: the novel algorithm not noly reduces the error rate dramaticlly but also increases the convergence rate tremendously of the algorithm.