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Extended Kernel Recursive Least Squares Algorithm
2009
IEEE Transactions on Signal Processing
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Index Terms Extended recursive least squares, Kalman filter, kernel methods, reproducing kernel Hilbert spaces. ...
This paper presents a kernelized version of the extended recursive least squares (EX-KRLS) algorithm which implements for the first time a general linear state model in reproducing kernel Hilbert spaces ...
A REVIEW OF RECURSIVE LEAST SQUARES TECHNIQUES We start with a review on recursive least squares, kernel recursive least squares, extended recursive least squares and general kernel methods. ...
doi:10.1109/tsp.2009.2022007
fatcat:kupa7zogrzcnbn5jwx2dsg256y
Prediction of Time Series Empowered with a Novel SREKRLS Algorithm
2021
Computers Materials & Continua
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For the unforced dynamical non-linear state-space model, a new Q1 and efficient square root extended kernel recursive least square estimation algorithm is developed in this article. ...
Multiple experiments are carried out to validate the reliability, effectiveness, and applicability of the proposed algorithm and with different noise levels compared to the Extended kernel recursive least-squares ...
Conclusion The proposed algorithm offers an enhanced square root algorithm called Extended Kernel Recursive Least Square (EKRTS). ...
doi:10.32604/cmc.2021.015099
fatcat:efbli2hbjzhnzencnmodimx3ji
Kernel recursive least squares-type neuron for nonlinear equalization
2013
2013 21st Iranian Conference on Electrical Engineering (ICEE)
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A new kernel recursive least square-type neuron (NKRLS) equalizer is proposed which improves aforementioned nonlinear methods problems such as, classical training algorithm drawbacks to parameter definition ...
NKRLS cosnsists of Kenel recursive least square followed by a simple neuron. In the first part of paper the new proposed KRLS-type neuron algorithm is introduced. ...
KRLS has been Recently a very hot research area of regression tasks that results in works such as sliding window kernel recursive least square (SW_KRLS) [10] , extended kernel recursive least square ( ...
doi:10.1109/iraniancee.2013.6599721
fatcat:oahri32avnbnplxvgqws2lzipy
Interval Arithmetic based Adaptive Filtering Technique for Removal of Noise in Audio Signal
2020
International journal of recent technology and engineering
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The three adaptive filters algorithm used for comparison with the obtained results are Least Mean Square (LMS), Recursive Mean Square (RMS) filters and Kernel based filters. ...
The proposed work focuses on the enhancement of audio signal quality by cancelling the noise using interval analysis (arithmetic). ...
Adaptive kernel filters are being used within the ALE and ANC structures and are basically used in the linear algorithms such as the Recursive Least Squares (RLS) and the Least Mean Square (LMS) algorithms ...
doi:10.35940/ijrte.e6311.059120
fatcat:rixhxvzvbzanhh63cth6eohowa
Kernel fractional affine projection algorithm
2015
Applied Informatics
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recursive least squares (KRLS) (Engel et al. 2004; Liu et al. 2015) and extended kernel recursive least squares (Ex-KRLS) (Liu et al. 2009) algorithms. ...
Also the performance is validated in comparison with the least mean square algorithm, kernel least mean square algorithm, affine projection algorithm and kernel affine projection algorithm. ...
Raja and Qureshi introduced fractional least mean square algorithm (FLMS) (Zahoor and Qureshi 2009) for their work regarding system identification. ...
doi:10.1186/s40535-015-0015-5
fatcat:dixaw55y3fdfjesbccfbt4ctve
Speech Enhancement using Affine Projection Algorithm and Normalized Kernel Affine Projection Algorithm
2014
International Journal of Computer Applications
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The computer simulations are performed using NOIZEUS speech corpus for different SNR values using Affine projection (APA), Kernel Affine projection (KAPA), Recursive least square (RLS), Kernel least mean ...
This paper emphasize on enhancement of noisy speech by using Affine Projection Algorithm (APA) and Kernel Affine Projection Algorithm (KAPA). ...
Kernel adaptive filters include kernel least mean square, kernel affine projection algorithms, kernel recursive least squares, extended kernel recursive least squares and kernel Kalman filter. ...
doi:10.5120/17515-8075
fatcat:qncvbkvlrzfhhhbyzt2cxmdn4q
Recursive Minimum Complex Kernel Risk-Sensitive Loss Algorithm
2018
Entropy
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Simulation results verify that the proposed RMCKRSL out-performs the MCCC, generalized MCCC (GMCCC), and traditional recursive least squares (RLS). ...
Therefore, in this paper we propose a recursive complex KRSL algorithm called the recursive minimum complex kernel risk-sensitive loss (RMCKRSL). ...
MCCC shows an obvious advantage over the least absolute deviation (LAD) [22] , complex least mean square (CLMS) [23] , and recursive least squares (RLS) algorithms [24] . ...
doi:10.3390/e20120902
pmid:33266626
fatcat:kmwjdq5s4zbw3lqltct4h4h33a
Multi-kernel probability distribution regressions
2015
2015 International Joint Conference on Neural Networks (IJCNN)
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kernel regression algorithm, such as kernel recursive least squares (KRLS). ...
The numerical simulations on synthetic data obtained via Gaussian mixtures show that the proposed approach outperforms existing probability distribution (DR) regression algorithms by achieving smaller ...
RKHS methods, such as kernel recursive least square (KRLS) [9] , kernel least mean square (KLMS) [10], quantized kernel recursive least square (QKRLS) [11] and quantized kernel least square (QKLMS) ...
doi:10.1109/ijcnn.2015.7280577
dblp:conf/ijcnn/ZhuWLF15
fatcat:s4hkikoqyfgudmhgocz4b47kvi
Sliding windows and lattice algorithms for computing QR factors in the least squares theory of linear prediction
1990
IEEE Transactions on Acoustics Speech and Signal Processing
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Least Squares The least squares solution for a in Ya "" 0, with the constraint ao = I is 0, ... by removing some of the equations, or equivalently by removing some of the prediction error values on the ...
Sliding Windows and Lattice Algorithms for Computing QR Factors in the Least Squares Theory of Linear Prediction CEDRIC J. DEMEURE AND LOUIS L. ...
doi:10.1109/29.52714
fatcat:yqpjycrlojgdte2fauctkfwnfe
Nonlinear System Identification using a New Sliding-Window Kernel RLS Algorithm
2007
Journal of Communications
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In this paper we discuss in detail a recently proposed kernel-based version of the recursive least-squares (RLS) algorithm for fast adaptive nonlinear filtering. ...
The resulting kernel RLS algorithm is applied to several nonlinear system identification problems. ...
In case of linear problems, the well-known recursive least-squares (RLS) algorithm [10] can be used, which calculates the solution of the regularized LS problem (3) in a recursive manner, based on the ...
doi:10.4304/jcm.2.3.1-8
fatcat:7ecwf3wtw5h33k7hjmmo5qttaa
Convergence analysis of kernel LMS algorithm with pre-tuned dictionary
2014
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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The kernel least-mean-square (KLMS) algorithm is an appealing tool for online identification of nonlinear systems due to its simplicity and robustness. ...
This theoretical analysis paves the way for future investigations on KLMS dictionary design. ...
The kernel recursive least-squares (KRLS) algorithm was introduced in [2] . The sliding-window KRLS and the extended KRLS algorithms were derived in [3, 4] , respectively. ...
doi:10.1109/icassp.2014.6855006
dblp:conf/icassp/ChenGRB14
fatcat:2mtw4dcgj5barjt7hg5izfqczi
Convergence analysis of kernel LMS algorithm with pre-tuned dictionary
[article]
2013
arXiv
pre-print
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The kernel least-mean-square (KLMS) algorithm is an appealing tool for online identification of nonlinear systems due to its simplicity and robustness. ...
This theoretical analysis paves the way for future investigations on KLMS dictionary design. ...
The kernel recursive least-squares (KRLS) algorithm was introduced in [2] . The sliding-window KRLS and the extended KRLS algorithms were derived in [3, 4] , respectively. ...
arXiv:1310.8618v1
fatcat:uetdnff3pzgl3gsa2auakhu52i
Bootstrapping Particle Filters using Kernel Recursive Least Squares
2007
2007 IEEE Aerospace Conference
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This paper addresses this problem, describing an algorithm that combines Kernel Recursive Least Squares and particle filtering to learn a functional approximation for the measurement mechanism whilst generating ...
Although particle filters are extremely effective algorithms for object tracking, one of their limitations is a reliance on an accurate model for the object dynamics and observation mechanism. ...
Kernel Recursive Least Squares The Kernel Recursive Least Squares algorithm was introduced in [8] and has a conceptual foundation related to Principle Component Analysis and Support Vector Machines. ...
doi:10.1109/aero.2007.353043
fatcat:amxng4gdf5eb5glrnnskrni7uy
Operator-valued kernel recursive least squares algorithm
2015
2015 23rd European Signal Processing Conference (EUSIPCO)
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The paper develops recursive least square algorithms for nonlinear filtering of multivariate or functional data streams. The framework relies on kernel Hilbert spaces of operators. ...
The results generalize to this framework the kernel recursive least squares developed in the scalar case. ...
The contributions of this paper are two operator-valued kernel recursive least square algorithms, ovkRLS, especially for multivariate and functional data filtering applications. ...
doi:10.1109/eusipco.2015.7362810
dblp:conf/eusipco/AmblardK15
fatcat:ndwtfnzi4rd7nayorlaryvvavy
Kernel Least Mean Kurtosis Based Online Chaotic Time Series Prediction
2013
Chinese Physics Letters
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Based on the kernel methods and the nonlinear feature of chaotic time series, we develop a new algorithm called kernel least mean kurtosis (KLMK) by applying the kernel trick to the least mean kurtosis ...
Simulation results show that the performance of KLMK is better than those of LMK and the kernel least mean square (KLMS) algorithm. ...
Typical examples of KAF algorithms include KLMS, kernel recursive least squares (KRLS) [9] and the kernel affine projection algorithm (KAPA). ...
doi:10.1088/0256-307x/30/11/110505
fatcat:ux4yyqkmevdpdme26zwnljomru
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