Model and Algorithm of Dual Symmetrical Neural Networks and Its Application in Information Fusion

General neural networks always converge to local optimal position when solving global optimal problem but dual symmetrical neural networks can overcome this shortcoming . The model and algorithms that dual symmetrical neural networks is used to solve direction finding (DF) and frequency measurement are presented in this paper, dual symmetrical neural networks can solve global optimal problem while general neural networks is used to solve global optimal problem always do not succeed because it always converge to local optimal position. Result of software simulation demonstrates this methods is viable.