24,492 Hits in 4.9 sec

Extended Kernel Recursive Least Squares Algorithm

Weifeng Liu, Il Park, Yiwen Wang, J.C. Principe
2009 IEEE Transactions on Signal Processing  
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

Bilal Shoaib, Yasir Javed, Muhammad Adnan Khan, Fahad Ahmad, Rizwan Majeed, Muhammad Saqib Nawaz, Muhammad Adeel Ashraf, Abid Iqbal, Muhammad Idrees
2021 Computers Materials & Continua  
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

Mohammed Naseri Tehrani, Majid Shakhsi, Hossein Khoshbin
2013 2013 21st Iranian Conference on Electrical Engineering (ICEE)  
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  
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

Bilal Shoaib, Ijaz Mansoor Qureshi, Shafqat Ullah Khan, Sharjeel Abid Butt, Ihsan ul haq
2015 Applied Informatics  
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

Kavita R.Jadhav, Mrinal R. Bachute, R. D. Kharadkar
2014 International Journal of Computer Applications  
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

Guobing Qian, Dan Luo, Shiyuan Wang
2018 Entropy  
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

Pingping Zhu, Hongchuan Wei, Wenjie Lu, Silvia Ferrari
2015 2015 International Joint Conference on Neural Networks (IJCNN)  
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

C.J. Demeure, L.L. Scharf
1990 IEEE Transactions on Acoustics Speech and Signal Processing  
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

Steven Van Vaerenbergh, Javier Vía, Ignacio Santamaría
2007 Journal of Communications  
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

Jie Chen, Wei Gao, Cedric Richard, Jose-Carlos M. Bermudez
2014 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
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]

Jie Chen and Wei Gao and Cédric Richard and Jose-Carlos M. Bermudez
2013 arXiv   pre-print
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

Boris Oreshkin, Mark Coates
2007 2007 IEEE Aerospace Conference  
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

P. O. Amblard, H. Kadri
2015 2015 23rd European Signal Processing Conference (EUSIPCO)  
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

Hua Qu, Wen-Tao Ma, Ji-Hong Zhao, Ba-Dong Chen
2013 Chinese Physics Letters  
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
« Previous Showing results 1 — 15 out of 24,492 results