This paper focuses on interference suppression aspects for DS/CDMA (Direct Sequence / Code Division Multiple Access) LEO (Low Earth Orbit) satellite communication systems. The interference of other users represents a serious problem for LEO satellite CDMA systems. The application of interference suppression systems is a promising approach to mitigate the multiuser problem. With the concentratio...

In this paper we provide a thorough ser( symbol error rate) analysis of two well known adaptive algorithms for equalization based on a novel least squares reference model that allows to treat the equalizer problem equivalently as system identification problem. An adaptive algorithm is a procedure for adjusting the parameters of an adaptive filter to minimize a cost function chosen for the task ...

This paper presents a simple and easy implementable Least Mean Square (LMS) type approach for frequency estimation of three phase power system in an unbalanced condition. The proposed LMS type algorithm is based on a second order recursion for the complex voltage derived from Clarke's transformation which is proved in the paper. The proposed algorithm is real adaptive filter with real parameter...

For the ANSYS CFD codes CFX and Fluent coupling links to several 1D codes exist allowing for a wide range of multi-physics applications. As an example, a flexible coupling infrastructure in terms of supported multiphysics coupling conditions between ANSYS CFX and LMS AMESim is outlined. Examples of the wide range of coupling solutions of ANSYS CFD (CFX and Fluent) and coupled 1D-3D applications...

| Based on the least mean squares (LMS) algorithm , the LMS spectrum analyzer can be used to re-cursively calculate the discrete Fourier transform (DFT) of a sliding window of data. In this paper, we compare the LMS spectrum analyzer with the straightforward non-adaptive implementation of the recursive DFT. In particular , we demonstrate the robustness of the LMS spectrum analyzer to the propag...

This work presents a new variation of the commonly used Least Mean Squares Algorithm (LMS) for the identification of sparse signals with an a-priori known sparsity using a hard threshold operator in every iteration. It examines some useful properties of the algorithm and compares it with the traditional LMS and other sparsity aware variations of the same algorithm. It goes on to examine the app...

In this paper we present a general formalism for the establishment of the family of selective partial update affine projection algorithms (SPU-APA). The SPU-APA, the SPU regularized APA (SPU-R-APA), the SPU partial rank algorithm (SPU-PRA), the SPU binormalized data reusing least mean squares (SPU-BNDR-LMS), and the SPU normalized LMS with orthogonal correction factors (SPU-NLMS-OCF) algorithms...

We present a method to deal with adaptive noise cancelling based on independent component analysis (ICA). Although popular least-mean-squares (LMS) algorithm removes noise components based on second-order correlation, the proposed ICA-based algorithm can utilize higher-order statistics. Additionally, extending to transform-domain adaptive filtering (TDAF) methods, normalized ICA-based algorithm...

This paper applies the new least mean squares (LMS) adaptive algorithm, which is circulantly weighted LMS (CLMS), in distributed networks based on incremental strategy. Thedistributed CLMS (dCLMS) algorithm is optimized with respect to approximate a priori knowledge of input autocorrelation signals from all nodes in the network. In comparison with dLMS, the dCLMS adaptive algorithm has faster c...