Fast adaptive RLS algorithms: a generalized inverse approach and analysis

Qiao, Sanzheng

doi:10.1109/78.136559

Cited by 15 publications

(6 citation statements)

References 9 publications

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“…𝑒(𝑘) = 𝑦 𝑚𝑒𝑠 (𝑘) − 𝑦(𝑘) is the error between estimated and measured outputs. For the weight adaptation algorithm, we choose the recursive least squares (RLS) algorithm [21], [22]. It is a quadratic method which consists in minimizing a quadratic function of error e(k) between the measured signal and the model.…”

Section: Principle Of the Adaline Methodsmentioning

confidence: 99%

A comprehensive overview of the ADALINE method applied to rapid voltage sags detection in multi-motors drive systems

2022

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Several strategies have been developed for identifying power quality issues, monitoring them, and compensating for relevant disturbances. In this field, online estimate of amplitudes and phase angles of network voltages and currents is commonly used. The adaptive linear neuron (ADALINE)-based voltage sag detection algorithm with least mean square (LMS) adaptation allows for rapid convergence of estimate techniques based on artificial neural networks (ANN). This approach has the advantage of being straightforward to implement on hardware and based on simple calculations (essentially multiply and accumulate "MAC"). This paper gives a comparison of the performance of two ADALINE approaches ("with" and "without" error supervision) for detecting and estimating voltage dips. The described techniques and models of a two-coupled motor system were implemented in MATLAB/Simulink/SimPowerSystems to run simulations under various fault scenarios in order to create the three-phase voltage sag alarm signal. The simulation outcomes are presented and debated.

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Section: Principle Of the Adaline Methodsmentioning

confidence: 99%

A comprehensive overview of the ADALINE method applied to rapid voltage sags detection in multi-motors drive systems

2022

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“…To estimate the best weight of the array (Godara, 1997a), efficient algorithms as LMS (Least Mean Squares) (Clarkson & White, 1987) and RLS (Recursive Least Squares) (Qiao, 1991) can be used. Due to this control over the radiation pattern envisaging a better management of the system, it is also possible to form dynamic cells using the multiple beams.…”

Section: Smart Receiversmentioning

confidence: 99%

Mobile and Wireless Communications

Tc¹,

Omidyar²

2003

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Her research interests include cooperative relay network, OFDMA resource allocation, adaptive antenna arrays, sensor networks, and signal processing for telecommunication applications.Fumiyuki Adachi received the B.S. and Dr. Eng. degrees in electrical engineering from Tohoku University, Sendai, Japan, in 1973, respectively. In April 1973, he joined the Electrical Communications Laboratories of Nippon Telegraph & Telephone Corporation (now NTT) and conducted various researches on digital cellular mobile communications. From July 1992 to December 1999, he was with NTT Mobile Communications Network, Inc. (now NTT DoCoMo, Inc.), where he led a research group on Wideband CDMA for 3G systems. Since January 2000, he has been with Tohoku University, Sendai, Japan, where he is a Professor at the Dept. of Communications Engineering, Graduate School of Engineering. His research interest is in the area of wireless signal processing (multiaccess, equalization, antenna diversity, adaptive transmission, channel coding, etc.

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“…The RLS algorithm is one of the most popular techniques [4], [5], [6]. It offers superior speed of convergence compared to LMS algorithm and its variations, especially in highly correlated environments.…”

Section: Introductionmentioning

confidence: 99%

Recursive inverse adaptive filtering algorithm

Ahmad¹,

Kükrer²,

Hocanin³

2009

2009 Fifth International Conference on Soft Computing, Computing With Words and Perceptions in System Analysis, Decision and Co

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In this paper, a new FIR adaptive filtering algorithm is introduced. This algorithm is based on the Quasi-Newton (QN) optimization algorithm. The approach uses a variable step-size in the coefficient update equation that leads to an improved performance. The simulation results show that the algorithm has very similar performance to the Robust Recursive Least Squares Algorithm (RRLS) while performing better than the Transform Domain LMS with Variable Step-Size (TDVSS) in stationary environments. The algorithm is tested in Additive White Gaussian Noise (AWGN) and Correlated Noise environments.

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Fast adaptive RLS algorithms: a generalized inverse approach and analysis

Cited by 15 publications

References 9 publications

A comprehensive overview of the ADALINE method applied to rapid voltage sags detection in multi-motors drive systems

A comprehensive overview of the ADALINE method applied to rapid voltage sags detection in multi-motors drive systems

Mobile and Wireless Communications

Recursive inverse adaptive filtering algorithm

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