Results 211 to 220 of about 49,604 (295)

Improved parameter identification and state-of-charge estimation for lithium-ion battery with fixed memory recursive least squares and sigma-point Kalman filter

, 2021
Accurate estimation of state-of-charge (SOC) of lithium-ion batteries (LIBs) is one of the important tasks of the on-board battery management system (BMS) to ensure the safe, efficient and reliable operation of electric vehicle power battery packs.
Changcheng Sun, Huipin Lin, Hui Cai, Mingyu Gao, Chunxiang Zhu, Zhiwei He   +5 more
semanticscholar   +1 more source

Unbiased recursive least squares identification methods for a class of nonlinear systems with irregularly missing data

International Journal of Adaptive Control and Signal Processing, 2023
Missing data often occur in industrial processes. In order to solve this problem, an auxiliary model and a particle filter are adopted to estimate the missing outputs, and two unbiased parameter estimation methods are developed for a class of nonlinear ...
Wenxuan Liu, Meihang Li
semanticscholar   +1 more source

STAR recursive least square lattice adaptive filters

IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 1997
The recursive least square lattice (LSL) algorithm based on the newly developed scaled tangent rotations (STAR) is derived. Similar to other recursive least square lattice algorithms for adaptive filtering, this algorithm requires only O(N) operations.
null Yuet Li, K.K. Parhi
openaire   +1 more source

Data-Reuse Recursive Least-Squares Algorithms

IEEE Signal Processing Letters, 2022
There are different strategies to improve the overall performance of the recursive least-squares (RLS) adaptive filter. In this letter, we focus on the data-reuse approach, aiming to improve the convergence rate/tracking of the algorithm by reusing the ...
C. Paleologu, J. Benesty, S. Ciochină
semanticscholar   +1 more source

A Proportionate Recursive Least Squares Algorithm and Its Performance Analysis

IEEE Transactions on Circuits and Systems - II - Express Briefs, 2021
The proportionate updating (PU) mechanism has been widely adopted in least mean squares (LMS) adaptive filtering algorithms to exploit the system sparsity.
Zhen Qin, Jun Tao, Yili Xia
semanticscholar   +1 more source

Reduced-Complexity Constrained Recursive Least-Squares Adaptive Filtering Algorithm

IEEE Transactions on Signal Processing, 2012
A linearly-constrained recursive least-squares adaptive filtering algorithm based on the method of weighting and the dichotomous coordinate descent (DCD) iterations is proposed. The method of weighting is employed to incorporate the linear constraints into the least-squares problem.
R. Arablouei, Kutluyil Dogancay
openaire   +2 more sources

Quaternion kernel recursive least-squares algorithm

Signal Processing, 2021
Various kernel-based algorithms have been successfully applied to nonlinear problems in adaptive filters over the last two decades. In this paper, we study a kernel recursive least squares (KRLS) algorithm in the quaternion domain.
Gang Wang, Jingci Qiao, R. Xue, Bei Peng
semanticscholar   +1 more source

Fast, recursive-least-squares transversal filters for adaptive filtering

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1984
Fast, fixed-order recursive least-squares (FORLS) algorithms for updating the parameters in linear regression models are presented. The algorithms are derived by using a geometrical approach (more exactly, certain formulas for updating projection operators). Both scalar and multichannel models are considered.
Cioffi, John M., Kailath, Thomas
openaire   +2 more sources

On least-squars design of recursive digital filters

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1976
Time-domain methods for the design of recursive digital filters using a squared error criterion are compared with a frequency-domain technique. Levy's method, which has been used to estimate transfer functions of continuous-time systems is modified to obtain design equations for digital filters.
K. Shenoi, M. Narasimha, A. Peterson
openaire   +1 more source

Recursive least squares filtering under stochastic computational errors

2013 Asilomar Conference on Signals, Systems and Computers, 2013
Power efficiency and reliability are two issues facing digital signal processing (DSP) systems designed using CMOS and nanoscale process technologies. Power saving techniques like voltage overscaling (VOS) in CMOS technologies and the reliability issues in nanoscale processes make these systems susceptible to transient errors.
C. Radhakrishnan, A. C. Singer
openaire   +1 more source