This paper deals with the problem of Adaptive Noise Cancellation (ANC) for the speech signal corrupted with an additive white Gaussian noise. After explaining the least Mean Square (LMS)-based adaptive filter and Kalman filter, it examine the hybrid Kalman-based LMS (KNLMS) technique for adaptation of the ANC. The proposed technique suggests a way to normalize LMS algorithm using Kalman filter....

This paper presents an efficient design and implementation of low area, high speed Adaptive filter based on Distributed Arithmetic (DA) Scheme. An enhanced NLMS algorithm has been proposed for the adaptive noise cancellation filter design. The computation speed of the proposed NLMS system is relatively high due to preallocation of memory for variables in enhanced Normalized LMS algorithm.The pr...

The block subband adaptive algorithm in [1] has illustrated significant improvement in performance over the NLMS and other frequency domain adaptive algorithms. However, it is known that block processing algorithms have lower tracking capabilities than the their sample-by-sample counterparts. The Fast Affine Projection (FAP) algorithm [2] also outperforms the NLMS with a slight increase in comp...

This paper investigates the multiple relay codedcooperation scheme based on asymmetric turbo code (ATC) with multiple receive antennas over Rayleigh block fading channels. An encoding scheme based on ATC is proposed for coded-cooperation, i.e. distributed asymmetric turbo code (DATC). The code matched interleaver (CMI) is selected by a rigorous comparison with a uniform-random interleaver (URI)...

Least mean square (LMS) based adaptive algorithms have been attracted much attention since their low computational complexity and robust recovery capability. To exploit the channel sparsity, LMS-based adaptive sparse channel estimation methods, e.g., L1-norm LMS or zero-attracting LMS (sparse LMS or ZA-LMS), reweighted zero attracting LMS (RZA-LMS) and Lp-norm LMS (LP-LMS), have been proposed b...

The electrocardiogram (ECG) is the graphical representation of heart’s functionality. It is an important tool used for the diagnosis of cardiac abnormalities. ECG signals are usually weak and susceptible to external noise and interference. Adaptive filter is a good tool to reduce the influence of ambient noise/interference on the ECG signals. Adaptive filter uses Least mean squares (LMS) algori...

We have presented an adaptive algorithm similar to both the signerror and NLMS adaptive algorithms that is capable of reducing the geomagnetic noise present in magnetic anomaly detection systems. Through both theory and application of this algorithm to actual MAD flight data, we have proven this algorithm’s insensitivity to transients in the desired response, with a corresponding improvement in...

In this paper, adaptive filtering is adopted for active automotive engine vibration isolation where both transient and stationary engine internal excitations as well as structure flexibility are considered. The adaptive filtering problem is formulated using a linear regression model representation. This allows for an application of a general family of state-of-the-art recursive parameter estima...

Typical approaches to acoustic echo cancellation (AEC) in mobile telephones employ adaptive linear algorithms, such as the normalized least mean squares (NLMS) algorithm. Smaller, cheaper components on these devices introduce nonlinearities into the echo path, which adversely affect performance of linear AEC systems and necessitate means of nonlinear compensation. Memoryless nonlinear blocks th...

The program ”Filtering and Identification Tool” designed for MATLAB provides an easy to handle tool for linear system identification of continuous time domain systems. But also discrete time models may be identified. The only property the process model must fulfill is that it has to be linear in the parameters. A graphical user interface guides the research engineer through all steps. As most o...