This paper presents a new algorithm that can solve the problem of selecting appropriate update step size in the LMS algorithm. The proposed algorithm, called a Complementary Pair LMS (CP-LMS) algorithm, consists of two adaptive lters with di erent update step sizes operating in parallel, one lter re-initializing the other with the better coe cient estimates whenever possible. This new algorithm...

The objective of this letter is to analyze the effects of frequency mismatch for an adaptive algorithm that becomes the Filtered-X LMS algorithm when the reference signals are purely sinusoidal. The Filtered-X LMS algorithm is often used for active control of acoustic noise. For the case of sinusoidal noise sources, if there is a deviation between the frequency used in the adaptive algorithm an...

The wavelet transform-domain least-mean square (WTDLMS) algorithm uses the self-orthogonalizing technique to improve the convergence performance of LMS. In WTDLMS algorithm, the trade-off between the steady-state error and the convergence rate is obtained by the fixed step-size. In this paper, the WTDLMS adaptive algorithm with variable step-size (VSS) is established. The step-size in each subf...

background: coronary angiography, albeit a safe procedure, may cause serious complications especially in patients with left main stenosis (lms). this study was designed to investigate the efficacy of workload achieved by exercise tolerance test (ett) in predicting lms in candidates for coronary angiography. methods: a total of 743 patients with a positive ett who subsequently underwent cardiac ...

This paper briefly discussed the principle of the linear constraints minimum variance (LCMV) algorithm and the least mean square (LMS) algorithm on the basis of the construction of an uniform circular antenna array. Then it compared the parameters of the two, such as signal-to-noise ratio, bit error rate, the average error, convergence rate, and so on, and then it was simulated by MATLAB. The s...

Nonlinear adaptive filtering techniques, based on the Volterra model, are widely used for the nonlinearities identification in many applications. This paper proposes a new implementation of the third order LMS Volterra filter. A third order nonlinear system with memory is identified using the new LMS algorithm implementation for the Volterra kernels estimation. The accuracy of the proposed algo...

In this paper, we are to develop a second-order LMS-type adaptive equalizer to reduce distortions of data transmission over analog telephone channels due the channel impulse response and inter-symbol interference (ISI). A novel approach for updating the linear and quadratic coefficients vectors of a second-order Volterra filter is presented. The innovative features of this algorithm provide dis...

The Filtered-x LMS algorithm has been an essential component of many industrial active control systems. This algorithm can be used in mono-channel, as well as multi-channel systems. One of the drawbacks of the multi-channel Filtered-x LMS algorithm is that its convergence speed depends on the autocorrelation and intercorrelation of the different filtered reference signals and can be very slow. ...

This paper introduces a cascade d RLS-LMS predictor for predictive lossless audio coding applications. In this proposed predictor, a LMS predictor with large order is employed in order to capture the ample tonal and harmonic components of the audio signal for optimal prediction gain performance. Meanwhile, to solve the slow convergence problem of the LMS algorithm with colored inputs, a low-ord...

The convergence rate of the least-mean-square (LMS) algorithm deteriorates if the input signal to the filter is correlated. In a system identification problem, this convergence rate can be improved if the signal is white and/or if the system is sparse. We recently proposed a sparse transform domain LMS-type algorithm that uses a variable step-size for a sparse system identification. The propose...