Standard least mean square/fourth (LMS/F) is a classical adaptive algorithm that combined the advantages of both least mean square (LMS) and least mean fourth (LMF). The advantage of LMS is fast convergence speed while its shortcoming is suboptimal solution in low signal-to-noise ratio (SNR) environment. On the contrary, the advantage of LMF algorithm is robust in low SNR while its drawback is ...

This paper presents a new method for variable step size for LMS algorithm. The proposed algorithm is based on an absolute mean of estimation current and prior error vector. It is called New Varying Step Size LMS Algorithm (NVSSLMS). The main goal of this algorithm is performance enhancement of adaptive echo cancellation system. The proposed time varying step size method begins the learning proc...

A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped LMS, and uses a three-level quantization (+1, 0,−1) scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wi...

AbslrabTwo gradient descent adaptive algorithms are compared, the LMS algorithm and the LMSNewton algorithm. LMS is simple and practical, and is used in many applications worldwide. LMWewton is based on Newton's method and the LMS algorithm. LMSiNewton is optimal in the least squares sense. It maximizes the quality of its adaptive solution while minimizing the use of training dah. No other line...

This paper proposes a cascaded RLS-LMS predictor for lossless audio coding. In this proposed predictor, a high-order LMS predictor is employed to model the ample tonal and harmonic components of the audio signal for optimal prediction gain performance. To solve the slow convergence problem of the LMS algorithm with colored inputs, a low-order RLS predictor is cascaded prior to the LMS predictor...

1.0 Introduction For active noise control (ANC) systems, a common approach is to use adaptive FIR filters trained with the filtered-x LMS algorithm [1], for both feedforward systems and Internal Model Control (IMC) feedback systems, in monochannel or multichannel systems. Variations of the algorithm sometimes called the modified filtered-x LMS algorithm have been published [2], which can achiev...

Manuscript received December 10, 1999. Manuscript revised March 18, 2000. † The authors are with the Telecom Research Laboratory, Kyushu Matsushita Electric Co., Ltd., Fukuoka-shi, 812-8531 Japan. SUMMARY This paper proposes a fast and simple adaptive algorithm for MMSE (Minimum Mean Square Error) adaptive array antenna or MMSE combining diversity. This algorithm can be implemented with as a sm...

For the purpose of equalisation of rapidly time variant multipath channels, the RLS algorithm might provide better performance than the LMS algorithm. However, the RLS algorithm requires complicated operation to adapt the equaliser coe cients. In this paper, we derive a novel adaptive algorithm, amplitude banded LMS(ABLMS), and develop it as the adaptation procedure for a linear transversal equ...

An on-line transform domain Least Mean Square (LMS) algorithm based on a neural approach is proposed. A temporal Principal Component Analysis (PCA) network is used as an orthonormalization layer in the transform domain LMS filter. Since PCA learning is an on-line learning algorithm, an on-line transform domain LMS filter can be easily implemented. Moreover, a modified Kalman estimation, which c...