CAJ | 학술논문

在基于Lorentzian函数的变步长LMS自适应滤波算法的基础上，进行进一步改进，提出了一种新的自适应LMS滤波算法，通过建立新的误差信号e(n)与变步长因子μ(n)之间的关系，消除不相关噪声的影响。并用Matlab对其进行仿真验证，表明该算法解决了收敛速度和稳态误差之间的矛盾，在保证算法的计算复杂度较低的同时，使得算法的抗干扰能力进一步提高，适用于低信噪比条件下的信号提取及滤波，为实际应用提供了更大的灵活性。
재기우Lorentzian함수적변보장LMS자괄응려파산법적기출상，진행진일보개진，제출료일충신적자괄응LMS려파산법，통과건립신적오차신호e(n)여변보장인자μ(n)지간적관계，소제불상관조성적영향。병용Matlab대기진행방진험증，표명해산법해결료수렴속도화은태오차지간적모순，재보증산법적계산복잡도교저적동시，사득산법적항간우능력진일보제고，괄용우저신조비조건하적신호제취급려파，위실제응용제공료경대적령활성。
A new adaptive LMS filtering algorithm is proposed by improving the Lorentzian function-based variable step size LMS adaptive filtering algorithm. Through establishing the relationship between error signal e(n) and variable step size factorμ(n) to undo the uncorrelated noise. The algorithm is simulated by Matlab,and the results show that the improved algorithm has solved the contradiction between the convergence rate and steady-state error. The anti-interference ability of the algorithm is im-proved while guaranteeing the computational complexity is lower. It is suitable for low SNR signal extraction and filtering,and provides greater flexibility for the practical application.