Detect And Extract Weak Signal Embedden In Chaos Background

Since chaos signal is random and uncertainty, it is difficult for us to predict chaos signal.Combined genetic algorithm (GA) with Radial basis function(RBF) neural network, propsing effective solutions for solving this problem.Genetic algorithm is a kind of stochastic global parallel search algorithm, it has strong robustness. RBF neural network is a kind of three-layer feedforward neural network with single hidden layer. The RBF network configuration is formulated as a minimization problem with respect to the number of hidden layer nodes,the center locations and the connection weights. Traditional GA has the disavantage with premature convergence, and it only to find the optimal solution in a short period of time. In the present study, hubrid hierarchy genetic algorithms is introduced to configure to structure and parameters of RBF network,and use adaptive function to adjust the crossover and mutation probability.To use improved genetic algoithm training RBF neural network in singnal detection,built a improved RBF neural network in the context of a chaotic detector. At last,use Matlab simulation to verify the effectiveness of the method in the signal extraction and detection.