Suchergebnisse - "((\"kernel recursive least squares algorithm\") OR (\"kernel recursive past squares algorithm\"))"

Mixed-Precision Kernel Recursive Least Squares.

Autoren: Lee, JunKyu Nikolopoulos, Dimitrios S. Vandierendonck, Hans

Quelle: IEEE Transactions on Neural Networks & Learning Systems; Mar2022, Vol. 33 Issue 3, p1284-1298, 15p

Schlagwörter: OCEAN temperature, TIME series analysis, NONLINEAR regression, ONLINE education, MACHINE learning

Single‐image super‐resolution using online kernel adaptive filters.

Autoren: Anver, Jesna Parambil, Abdulla

Quelle: IET Image Processing (Wiley-Blackwell); Sep2019, Vol. 13 Issue 11, p1846-1852, 7p

Schlagwörter: IMAGE recognition (Computer vision), LEAST squares, IMPULSE response, ARTIFICIAL intelligence, ENCYCLOPEDIAS & dictionaries, ADAPTIVE filters

Research Progress on Intelligent System’s Learning, Optimization, and Control—Part II: Online Sparse Kernel Adaptive Algorithm.

Autoren: Tan, Fuxiao Guan, Xinping

Quelle: IEEE Transactions on Systems, Man & Cybernetics. Systems; Dec2020, Vol. 50 Issue 12, p5369-5385, 17p

Schlagwörter: ALGORITHMS, ADAPTIVE filters, HILBERT space, PRINCIPAL components analysis, KERNEL functions, KERNEL (Mathematics)

The Kernel Recursive Least-Squares Algorithm.

Autoren: Engel, Yaakov Mannor, Shie Meir, Ron

Quelle: IEEE Transactions on Signal Processing; Aug2004, Vol. 52 Issue 8, p2275-2285, 11p

Schlagwörter: ALGORITHMS, ALGEBRA, ONLINE data processing, KERNEL functions, COMPLEX variables, LEAST squares

Extended Kernel Recursive Least Squares Algorithm.

Autoren: Weifeng Liu Il Park Yiwen Wang et al.

Quelle: IEEE Transactions on Signal Processing; Oct2009, Vol. 57 Issue 10, p3801-3814, 14p, 4 Black and White Photographs, 2 Charts, 9 Graphs

Schlagwörter: KERNEL functions, HILBERT space, KALMAN filtering, ESTIMATION theory, RECURSIVE functions

Deep kernel recursive least-squares algorithm.

Autoren: Mohamadipanah, Hossein Heydari, Mahdi Chowdhary, Girish

Quelle: Nonlinear Dynamics; May2021, Vol. 104 Issue 3, p2515-2530, 16p

Kernel Recursive Least-Squares Algorithm.

Autoren: Haykin, Simon Liu, Weifeng Príncipe, José C.

Quelle: Kernel Adaptive Filtering: A Comprehensive Introduction; 2010, p94-123, 30p

Extended Kernel Recursive Least-Squares Algorithm.

Autoren: Haykin, Simon Liu, Weifeng Príncipe, José C.

Quelle: Kernel Adaptive Filtering: A Comprehensive Introduction; 2010, p124-151, 28p

Kernel Recursive Least-Squares Tracker for Time-Varying Regression.

Autoren: Van Vaerenbergh, Steven Lazaro-Gredilla, Miguel Santamaria, Ignacio

Quelle: IEEE Transactions on Neural Networks & Learning Systems; Aug2012, Vol. 23 Issue 8, p1313-1326, 14p

Schlagwörter: SIGNAL processing, KERNEL (Mathematics), ADAPTIVE filters, COMPUTATIONAL complexity, COMPUTER simulation

Using near-infrared spectroscopy to determine intramuscular fat and fatty acids of beef applying different prediction approaches.

Autoren: Barragán-Hernández, Wilson Mahecha-Ledesma, Liliana Burgos-Paz, William et al.

Quelle: Journal of Animal Science. Nov2020, Vol. 98 Issue 11, p1-10. 10p. 3 Charts, 2 Graphs.

Nonlinear adaptive filtering using kernel-based algorithms with dictionary adaptation.

Autoren: Saide, Chafic Lengelle, Régis Honeine, Paul et al.

Quelle: International Journal of Adaptive Control & Signal Processing. Nov2015, Vol. 29 Issue 11, p1391-1410. 20p.

Schlagwörter: *FILTERS & filtration, *KERNEL functions, *ALGORITHMS, *VECTORS (Calculus), *METHODOLOGY

Active impulsive noise control using maximum correntropy with adaptive kernel size.

Autoren: Lu, Lu Zhao, Haiquan

Quelle: Mechanical Systems & Signal Processing. Mar2017 Part A, Vol. 87, p180-191. 12p.

Schlagwörter: *NOISE control, *ACTIVE noise control, *KERNEL functions, *LEAST squares, *NOISE

Sequential Learning with LS-SVM for Large-Scale Data Sets.

Autoren: Kollias, Stefanos Stafylopatis, Andreas Duch, Włodzisław et al.

Quelle: Artificial Neural Networks - ICANN 2006 (9783540388715); 2006, p381-390, 10p

Probability Density Rank-Based Quantization for Convex Universal Learning Machines.

Autoren: Qin, Zhengda Chen, Badong Gu, Yuantao et al.

Quelle: IEEE Transactions on Neural Networks & Learning Systems; Aug2020, Vol. 31 Issue 8, p3100-3113, 14p

Schlagwörter: MACHINE learning, DATA distribution, PROBABILITY theory, DENSITY, VECTOR quantization

Multi-omics assists genomic prediction of maize yield with machine learning approaches.

Autoren: Wu, Chengxiu Luo, Jingyun Xiao, Yingjie

Quelle: Molecular Breeding; Feb2024, Vol. 44 Issue 2, p1-17, 17p

Schlagwörter: MACHINE learning, MULTIOMICS, RADIAL basis functions, SINGLE nucleotide polymorphisms, KERNEL functions

Alternative partial least-squares (PLS) algorithms.

Autoren: Lindgren, Fredrik Rännar, Stefan

Quelle: Perspectives in Drug Discovery & Design; Jan1998, Vol. 12-14 Issue 0, p105-113, 9p

Performance of pedigree and various forms of marker‐derived relationship coefficients in genomic prediction and their correlations.

Autoren: Solaymani, Samaneh Ayatollahi Mehrgardi, Ahmad Esmailizadeh, Ali et al.

Quelle: Journal of Animal Breeding & Genetics. Sep2020, Vol. 137 Issue 5, p423-437. 15p.

Schlagworte: Forecasting, Path analysis (Statistics), Genealogy, Information resources, Kinship, Heritability

Kernel Risk-Sensitive Mean p-Power Error Algorithms for Robust Learning.

Autoren: Zhang, Tao Wang, Shiyuan Zhang, Haonan et al.

Quelle: Entropy; Jun2019, Vol. 21 Issue 6, p588, 1p

Schlagwörter: MONTE Carlo method, KERNEL functions, ADAPTIVE filters, MACHINE learning, HILBERT space, EXPONENTIAL functions, SIGNAL processing

Prediction of Time Series Empowered with a Novel SREKRLS Algorithm.

Autoren: Shoaib, Bilal Javed, Yasir Khan, Muhammad Adnan et al.

Quelle: Computers, Materials & Continua; 2021, Vol. 67 Issue 2, p1413-1427, 15p

Schlagwörter: TIME series analysis, MATRIX inversion, ALGORITHMS, SQUARE root, LEAST squares, FORECASTING

This is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms—Theory and Practice.

Autoren: Harmany, Zachary T. Marcia, Roummel F. Willett, Rebecca M.

Quelle: IEEE Transactions on Image Processing; Mar2012, Vol. 21 Issue 3, p1084-1096, 13p

Schlagwörter: ALGORITHMS, RANDOM noise theory, LEAST squares, IMAGE reconstruction, APPROXIMATION theory, INVERSE problems, WAVELETS (Mathematics), SCIENTIFIC observation