Functional network and its application to extract information from chaotic communication

In chaotic communication system, the useful signal is hidden in chaotic signal, so the general method does not work well. Due to the random feature of chaotic signal, a functional network-based method is presented. In this method, the neural functions are selected from some complete function set for the functional network to reconstruct the chaotic signal, so the useful signal hidden in chaotic background is extracted. In addition, its learning algorithm is presented here and the example proves its good preformance.