Quadratic Rotation decomposition (QRD) based recursive least squares (RLS) algorithm can be used in variety of communication applications and its low complexity implementation can be of interest. In this paper we have presented an application of QRD based RLS algorithm using Coordinate Rotation by Digital Computer (CORDIC) operator for implementing an adaptive beamformer. FPGA resource estimate...

This paper deals with a method of quantifying the harmonic contribution each source to system voltage distortion. Assessing individual sources is essential for mitigating and managing levels. Harmonic contributions can be evaluated using principle superposition equivalent models sources. In general, parameters are estimated numerically because it difficult measure them directly. this paper, we ...

The performance of the Normalized Least Mean Square (NLMS) algorithm for adaptive filtering is dependent on the spectral flatness of the reference input. Thus, the standard NLMS algorithm does not perform well in Over-Sampled Subband Adaptive Filters (OS-SAFs) because colored subband signals are generated even for white input signals. Thus we propose the use of the Affine Projection Algorithm (...

We introduce a recursive adaptive group lasso algorithm for real-time penalized least squares prediction that produces a time sequence of optimal sparse predictor coefficient vectors. At each time index the proposed algorithm computes an exact update of the optimal `1,∞-penalized recursive least squares (RLS) predictor. Each update minimizes a convex but nondifferentiable function optimization ...

The study proposes an algorithm for noise cancellation by using recursive least square (RLS) and pattern recognition by using fusion method of Dynamic Time Warping (DTW) and Hidden Markov Model (HMM). Speech signals are often corrupted with background noise and the changes in signal characteristics could be fast. These issues are especially important for robust speech recognition. Robustness is...

Recursive Least Square (RLS) is one of the algorithms that can be used to update array weights in adaptive array antennas. Although the calculation load is large, it achieves fast convergence and is thus effective under fading environments; it shows great promise in mobile communication applications [1]. We first constructed a fully functional testbed in which the RLS algorithm is implemented u...

Recursive least-squares (RLS) algorithms are widely used in many applications, such as real-time signal processing, control and communications. In some regularization of the provides robustness enhances performance. Interestingly, updating parameter processing data continuously time is a desirable strategy to improve performance applications beamforming. While presented works literature assume ...

In the field of automatic control system design, adaptive inverse is a powerful control technique. It identifies the system model and controls automatically without having prior knowledge about the dynamics of plant. In this paper neural network based adaptive inverse controller is proposed to control a MIMO system. Multi layer perception and back propagation are combinedly used in this investi...

In this paper a brief overview of the Fast Transversal Recursive Least-Squares (FT-RLS) algorithm is provided. This algorithm is designed to provide similar performance to the standard RLS algorithm while reducing the computation order. This is accomplished by a combination of four transversal filters used in unison. Finite precision effects are also briefly discussed. Simulations are performed...

This paper studies the comparative tracking performance of the recursive least squares (RLS) and least mean square (LMS) algorithms for time-varying inputs, specifically for linearly chirped narrowband input signals in additive white Gaussian noise. It is shown that the structural differences in the implementation of the LMS and RLS weight updates produce regions where the LMS performance excee...