We present an efficient architecture for the implementation of delayed least mean square adaptive filter. We use a novel partial product generator and propose a strategy for optimized balanced pipelining across the time consuming combinational blocks of the structure .An efficient systolic architecture of the delayed least mean square adaptive filter based on the processing element We propose a...

The least-mean-squares (LMS) algorithm which updates the filter coefficients by a stochastic gradient descent approach is the most popular adaptive filtering one. In this paper we propose a novel amplitude banded (AB) technique with LMS on Godard (ABGodard) and Sato (ABSato) algorithms for the equalization of communication channels. The non-linear properties of the AB technique with LMS algorit...

We present an efficient architecture for the implementation of delayed least mean square adaptive filter. We use a novel partial product generator and propose a strategy for optimized balanced pipelining across the time consuming combinational blocks of the structure .An efficient systolic architecture of the delayed least mean square adaptive filter based on the processing element .We propose ...

This paper presents a new method based on adaptive filtering theory for superresolution restoration of continuous image sequences. The proposed methodology suggests least squares (LS) estimators which adapt in time, based on adaptive filters, least mean squares (LMS) or recursive least squares (RLS). The adaptation enables the treatment of linear space and time-variant blurring and arbitrary mo...

The demand for increased capacity in wireless communication networks has motivated recent research activities toward wireless systems that exploit the concept of smart antenna and space selectivity. Efficient utilization of limited radio frequency spectrum is only possible to use smart/adaptive antenna system. Smart antenna radiates not only narrow beam towards desired users exploiting signal p...

The Volterra series model, though a popular tool in modeling many practical nonlinear systems, suffers from the problem of over-parameterization, as too many coefficients need to be identified, requiring very long data records. On the other hand, often it is observed that of all the model coefficients, only a few are prominent while the others are relatively insignificant. The sparsity inherent...

The Performance comparison of Minimum Mean Square Error-based Adaptive Multi-User Detection (MUD) of Direct Sequence-Code Division Multiple Access (DS-CDMA) signals is considered. DS-CDMA is a popular multiple-access technology for wireless communication. But its performance is limited by multiple-access interference (MAI) and multipath distortion. Adaptive techniques, such as least mean square...

Since both the least mean-square (LMS) and least mean-fourth (LMF) algorithms suffer individually from the problem of eigenvalue spread, so will the mixed-norm LMS-LMF algorithm. Therefore, to overcome this problem for the mixed-norm LMS-LMF, we are adopting here the same technique of normalization (normalizing with the power of the input) that was successfully used with the LMS and LMF separat...

ÐIn an earlier work, we have introduced the problem of reconstructing a super-resolution image sequence from a given low resolution sequence. We proposed two iterative algorithms, the R-SD and the R-LMS, to generate the desired image sequence. These algorithms assume the knowledge of the blur, the down-sampling, the sequences motion, and the measurements noise characteristics, and apply a seque...