The Study On Algorithms And Applications Of Adaptive Filter

The research of adaptive filtering algorithms is one of the most active tasks in the field of modern signal processing. The goal that researchers are pursuing is to find an adaptive filtering algorithm that converges fast and has low arithmetic complexity. This paper aims at the adaptive filtering algorithms and their applications. The main works can be summarized as follows:1.Based on the adaptive filtering principle, several typical adaptive algorithms as well as their applications are introduced in this paper, and a comparison is made among these algorithms' characters.2.The author analyzes the performance of the conventional LMS(Least Mean Square) algorithm. And due to the fact that the convergent speed and steady-state error are affected by the fixed step-size in classical LMS algorithm, an improved algorithm is presented with normalized variable step-size. Computer simulation verifies the better performance of the new algorithm.3.The Quasi-Newton(QN) algorithm is modified and used in the adaptive filtering system with impulse noise in its desired signals. The new algorithm is proved to have better ability to suppress the impulsive noise.4.A comparison is made among some improved RLS(Recursive Least Squares) algorithms and their applications in channel identification and channel equalization.