Hopfield Neural Network with Chaotic Positive Feedback and Its Application in Binary Signal Blind Detection

This paper presents a blind signal detection algorithm based on linear Chaotic Positive Feedback Hopfield Neural Network (CPFHNN). The algorithm uses sequence with chaos initialization as the transmitting signal and utilizes the HNN with positive feedback to solve the quadratic programming performance function of blind detection and to achieve BPSK signal blind detection. This paper constructs a new energy function of CPFHNN and proves the stability of CPFHNN through simulation by configuring network parameters under asynchronous update mode and synchronous update mode. Compared with the literature without chaotic positive feedback Hopfield neural network blind signal detection algorithm, CPFHNN requires shorter receive data to reach the real global balance point, and reduces the calculation difficulty greatly and has a good quickness.