基于混合型神经网络的自适应盲信号分离算法

SEPARATION ALGORITHM FOR SELF-ADAPTIVE BLIND SIGNAL BASED ON MIXING NEURAL NETWORK MODEL

不同的神经网络模型及其算法对信号分离的效能会产生不同的影响,寻找高效简便的神经网络自适应盲信号分离算法是目前的研究方向。根据控制系统传输信号在线监测控制的要求,提出一种基于前馈与反馈混合型神经网络模型的自适应盲信号分离算法,并应用于传输信号的分离。计算机仿真实验的结果表明该算法的有效性和快速性。

Different neural network models and their algorithms will exert different influences on the efficiency of signal separate, h is a study direction at present to find high-efficient and simple blind signal separation algorithms. A self-adaptive blind signal separation algorithm based on feed-forward and feedback mixing neural network model is developed based on the requirement of online monitoring and controlling the system real-time transmittal signal, as presented in this paper, and it is applied in the separation of transmission signal. The result of the computer simulation experiments shows the validity and fastness of this algorithm.