Study of Improved LMS Algorithm Based on the Continuous Block Processing

In the hardware system based on the continuous data block processing, several blocks of data are processed by the Least Mean Square (LMS) algorithm to obtain multiple weight vectors. The hardware system performance will get bad sharply if these weight vectors undulate greatly. In this paper, an improved LMS algorithm based on the continuous block processing is proposed to solve the problem. Firstly an updated weight vector is calculated by LMS algorithm for one block of data. Then, this weight vector is multiplied by a complex coefficient to normalize itself to the updated weight vector corresponding to the last block of data, which realizes the normalization of the amplitude and phase. Then the normalized weight vector is used as the initial weight vector in the next iteration calculation for the next data block. After the above processing, the fluctuation of the updated weight vectors among the data blocks is decreased so that the related parameters of the system change steadily and the system stabilization is enhanced. Meanwhile the convergence speed is improved. The effectiveness and correctness of the proposed method have been verified by computer simulations at last.