Results 21 to 30 of about 768 (156)
Coupled Least Squares Identification Algorithms for Multivariate Output-Error Systems
Algorithms, 2017 This paper focuses on the recursive identification problems for a multivariate output-error system. By decomposing the system into several subsystems and by forming a coupled relationship between the parameter estimation vectors of the subsystems, two ...
Wu Huang, Feng Ding
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IEEE Access, 2020 Monitoring the state of health (SOH) for Li-ion batteries is crucial in the battery management system (BMS), for their efficient and safe use. Due to time-varying battery parameters and insufficient computation capability of the BMSs, computationally ...
Minho Kim, Kwangrae Kim, Soohee Han
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Adaptive Filtering for the Maternal Respiration Signal Attenuation in the Uterine Electromyogram
Sensors, 2022 The electrohysterogram (EHG) is the uterine muscle electromyogram recorded at the abdominal surface of pregnant or non-pregnant woman. The maternal respiration electromyographic signal (MR-EMG) is one of the most relevant interferences present in an EHG.
Daniela Martins +7 more
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IEEE Access, 2020 In this paper, we propose a channel sparsity aware sequential recursive least squares (sparse SEQ-RLS) algorithm for function expansion filters with applications in nonlinear echo cancellation.
Jean Jiang +2 more
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IEEE Access, 2023 This paper presents a data-driven adaptive steady state-integral-derivative (SS-ID) control algorithm that uses gradient descent and recursive least squares (RLS) with a forgetting factor.
Jeongwoo Lee, Kwangseok Oh
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IEEE AccessWe develop a recursive least squares (RLS) type algorithm with a minimax concave penalty (MCP) for adaptive identification of a sparse tap-weight vector that represents a communication channel.
Bowen Li +4 more
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Forward and backward RLS-DDCE processing in MIMO-OFDM spatial multiplexing receivers [PDF]
Advances in Radio Science, 2010 In this paper we present a novel approach in frequency domain channel estimation technique. Our proposal is based on the recursive least squares (RLS) algorithm combined with the decision making process called decision directed channel estimation (RLS ...
M. Muxfeldt, P. Beinschob, U. Zölzer
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Signal Processing, 1994 Abstract In this paper, we derive a new fast algorithm for Recursive Least-Squares (RLS) adaptive filtering. This algorithm is especially suited for adapting very long filters such as in the acoustic echo cancelation problem. The starting point is to introduce subsampled updating (SU) in the RLS algorithm. In the SU RLS algorithm, the Kalman gain and
Slock, Dirk T. M., Maouche, Karim
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International Journal of Adaptive Control and Signal Processing, Volume 40, Issue 3, Page 544-564, March 2026.This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
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IET Power Electronics, 2021 This paper presents a novel filtering algorithm for the resolver position signal based on recursive least squares (RLS) and phase‐locked loop (PLL). The proposed RLS‐PLL‐based algorithm designs a harmonic iterative estimation and elimination mechanism ...
Chuanqiang Lian +3 more
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