For SOC (state of charge) assessment techniques based on electrical circuit models, the parameters model are strongly biased by: battery aging, temperature, causing some errors in estimation SOC. One approach to solve this problem is update constantly. We suggest a new algorithm VRLS (variable recursive least squares) 2-resistor-capacitor (RC) network and estimate output voltage. compared squar...

This paper proves the effectiveness of Least Mean Square (LMS) estimation algorithm for estimation of power system harmonics, inter-harmonics and sub-harmonics of distorted signal. Accurate estimation can be achieved by this technique for harmonics, sub-harmonics and inter-harmonics estimation including possible variation in the signal such as change in amplitude when applied to a distorted pow...

Unlike feedforward neural networks (FFNN) which can act as universal function approximaters, recursive neural networks have the potential to act as both universal function approximaters and universal system approximaters. In this paper, a globally recursive neural network least mean square (GRNNLMS) gradient descent or a real time recursive backpropagation (RTRBP) algorithm is developed for a s...

In order to gain insights on equalization design in the wireless mobile communication systems, we compare the performance of several multi-channel MLSE equalizers which adaptively track the fast-fading channels. Commonly-used channel tracking schemes, Decision-Directed Recursive Least Square (DD/RLS), Per-Survivor Processing Recursive Least Square (PSP/RLS) and other reduced-complexity MLSE alg...

The authors present the parallel-hybrid recursive least square (PH-RLS) algorithm for an accurate self-mixing interferometric laser vibration sensor coupled with accelerometer under industrial conditions. Previously, this was achieved by using a conventional RLS to cancel parasitic vibrations where itself is not in stationary environment. This operates sequential mode and due its compute data-i...

A comparison study of different adaptive algorithms(Least Mean Square(LMS), Normalized Least Mean Square(NLMS), Delayed Least Mean Square(DLMS), Recursive Least Square(RLS), QR decomposition based RLS(QRDRLS), Affine Projection(AP) ) using Adaptive filter is presented in this paper. The paper focuses on these adaptive algorithms which are used to reduce the noise from the signal which is corrup...