The Global Positioning System (GPS) signals are very weak signal over wireless channels, so they are vulnerable to in-band interferences. Therefore, even a low-power interference can easily spoof GPS receivers. Among the variety of GPS signal interference, spoofing is considered as the most dangerous intentional interference. The spoofing effects can mitigate with an appropriate strategy in the...

Widrow proposed the least mean squares (LMS) algorithm, which has been extensively applied in adaptive signal processing and adaptive control. The LMS algorithm is based on the minimum mean squares error. On the basis of the total least mean squares error or the minimum Raleigh quotient, we propose the total least mean squares (TLMS) algorithm. The paper gives the statistical analysis for this ...

A new algorithm, the binormalized data-reusing least mean squares (LMS) algorithm is presented. The new algorithm has been found to converge faster than other LMS-like algorithms, such as the Normalized LMS algorithm and several data-reusing LMS algorithms, when the input signal is highly correlated. The computational complexity of this new algorithm is only slightly higher than a recently prop...

A fundamental relationship exists between the quality of an adaptive solution and the amount of data used in obtaining it. Quality is defined here in terms of “misadjustment,” the ratio of the excess mean square error (mse) in an adaptive solution to the min imum possible mse. The higher the misadjustment, the lower the quality is. The quality of the exact least squares solution is compared wit...

Inter-symbol interference if not taken care off may cause severe error at the receiver and the detection of signal becomes difficult. An adaptive equalizer employing Recursive Least Squares algorithm can be a good compensation for the ISI problem. In this paper performance of communication link in presence of Least Mean Square and Recursive Least Squares equalizer algorithm is analyzed. A Model...

The least-mean-squares (LMS) algorithm is the most popular algorithm in adaptive filtering. Several variable step-size strategies have been suggested to improve the performance of the LMS algorithm. These strategies enhance the performance of the algorithm but a major drawback is the complexity in the theoretical analysis of the resultant algorithms. Researchers use several assumptions to find ...

This paper explores the potential of several popular equalization techniques and proposes new approaches to overcome their disadvantages. Such as the conventional least-mean-square (LMS ) algorithm, the recursive least-squares ( RLS ) algorithm, the filtered-X LMS algorithm and their development. An H 2 optimal initialization has been proposed to overcome the slow convergence problem while keep...

The key objective of this paper is to provide an idea for VLSI Implementation of RLS algorithm for noise cancellation with real time analog inputs. In this paper, we present an efficient architecture for the implementation of distributed arithmetic based multiplier less adaptive filter. The throughput rate of update and concurrent implementation of filtering and weightupdate operations. The con...