"Sparse Linear Models Applied to Power Quality Disturbance Classification"

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Book	Author(s)	Year	Publisher
Applied linear regression models /	Neter, John.	[1996], ©1996.	Irwin,
Applied linear statistical models /	John Neter	[1996], ©1996.	Irwin,
Applied linear regression models	John Neter	1989	Irwin
Applied Linear Models with SAS	Daniel Zelterman	2010-05	Cambridge University Press
Generalized Linear Models: An Applied Approach	Ulf Olsson	2002	Studentlitteratur AB
Linear statistical models: an applied approach	Bruce L. Bowerman	1990	PWS-Kent Pub. Co.
Solving sparse linear systems with sparse backward error.	M. Arioli	1988	Courant Institute of Mathematical Sciences, New York University
Statistical Regression and Classification: From Linear Models to Machine Learning	Norman Matloff	2017	Routledge
Beyond Multiple Linear Regression: Applied Generalized Linear Models and Multilevel Models in R	Paul Roback; Julie Legler	2021	Routledge
Applied Regression Analysis and Generalized Linear Models	John Fox	April 2015	SAGE Publications, Inc
Applied regression analysis and generalized linear models /	Fox, John,; Fox, John,	c2008.	Sage,
Applied regression analysis, linear models, and related methods	Fox, John	1997	Sage Publications
Student solutions manual for use with Applied linear regression models, third edition and Applied linear statistical models, fourth edition	John Neter	1996	Irwin McGraw-Hill
Introduction to linear models	Joe H. Ward, John W. Tukey, Earl Jennings	1973	Prentice-Hall
Iterative methods for sparse linear systems /	Saad, Y.	[1996], ©1996.	PWS Pub. Co.,
Iterative methods for sparse linear systems /	Saad, Y.	[2003], ©2003.	SIAM,
Direct methods for sparse linear systems /	Davis, Timothy A.	c2006.	SIAM, Society for Industrial and Applied Mathematics,
Identification for linear electrical power system models	Thomas G. DeVille	1971	Massachusetts Institute of Technology
Linear Models	S. R. Searle	1971	John Wiley & Sons
Linear Models	Barry Kurt Moser	1996	Academic Press
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Sparse Linear Models Applied to Power Quality Disturbance Classification	Andrés F. López-Lopera; Mauricio A. Álvarez; Álvaro Á. Orozco	Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 21st Iberoamerican Congress, CIARP 2016, Lima, Peru, November 8–11, 2016, Proceedings	César Beltrán-Castañón; Ingela Nyström; Fazel Famili	1st ed. 2017	Springer International Publishing
Power Quality Disturbance Classification Using Transformer Network	Dar Hung Chiam; King Hann Lim	Cyber Warfare, Security and Space Research: First International Conference, SpacSec 2021, Jaipur, India, December 9–10, 2021, Revised Selected Papers	Sandeep Joshi; Amit Kumar Bairwa; Amita Nandal; Milena Radenkovic; Cem Avsar	1st ed. 2022	Springer International Publishing
13 Sparse Linear Models		Machine learning: a probabilistic perspective /	Murphy, Kevin P.,	©2012.	MIT Press,
Classification Models Applied to Uncertain Data	Yandry Quiroz; Willian Zamora; Alex Santamaria-Philco; Elsa Vera; Patricia Quiroz-Palma	Technology Trends: 4th International Conference, CITT 2018, Babahoyo, Ecuador, August 29–31, 2018, Revised Selected Papers	Miguel Botto-Tobar; Guillermo Pizarro; Miguel Zúñiga-Prieto; Mayra D’Armas; Miguel Zúñiga Sánchez	1st ed. 2019	Springer International Publishing
Power Quality Disturbance Detection and Classification Using Chirplet Transforms	Guo-Sheng Hu; Feng-Feng Zhu; Yong-Jun Tu	Simulated Evolution and Learning: 6th International Conference, SEAL 2006, Hefei, China, October 15-18, 2006, Proceedings	Tzai-Der Wang; Xiaodong Li; Xufa Wang	2006	Springer Berlin Heidelberg
Power Quality Disturbance Detection and Classification Using Chirplet Transfor		Simulated Evolution and Learning: 6th International Conference, SEAL 2006, Hefei, China, October 15-18, 2006. Proceedings	P. A. Whigham, G. Dick (auth.), Tzai-Der Wang, Xiaodong Li, Shu-Heng Chen, Xufa Wang, Hussein Abbass, Hitoshi Iba, Guo-Liang Chen, Xin Yao (eds.)	2006	Springer-Verlag Berlin Heidelberg
A Hybrid Intelligent Model for Power Quality Disturbance Classification	H. Malik; Paras Kaushal; Smriti Srivastava	Applications of Artificial Intelligence Techniques in Engineering: SIGMA 2018, Volume 2	Hasmat Malik; Smriti Srivastava; Yog Raj Sood; Aamir Ahmad	1st ed. 2019	Springer Nature Singapore
Linear models for classification		Deep Learning By Example: A hands-on guide to implementing advanced machine learning algorithms and neural networks	Ahmed Menshawy	2018	Packt Publishing
Linear Models for Classification		Gaussian processes for machine learning	Carl Edward Rasmussen	2006	MIT Press
Real-Time Power Quality Disturbance Classification Using Convolutional Neural Networks	Budi Yanto Husodo; Kalamullah Ramli; Eko Ihsanto; Teddy Surya Gunawan	Recent Trends in Mechatronics Towards Industry 4. 0: Selected Articles from iM3F 2020, Malaysia	Ahmad Fakhri Ab. Nasir; Ahmad Najmuddin Ibrahim; Ismayuzri Ishak; Nafrizuan Mat Yahya; Muhammad Aizzat Zakaria; Anwar P. P. Abdul Majeed	1st ed. 2022	Springer Nature Singapore
Land Use Classification with Sparse Models	Mohamed L. Mekhalfi; Farid Melgani; Yakoub Bazi; Naif Alajlan	Compressive Sensing of Earth Observations	C.H. Chen	2017	Routledge
Disturbance Models	Torkel Glad; Lennart Ljung	Control Theory	Torkel Glad; Lennart Ljung	2000	Routledge
disturbance power	Martin H. Weik	Computer Science and Communications Dictionary	Martin Weik	2001	Springer US
Linear Programming Models for Classification	Paul A. Rubin	Encyclopedia of Optimization	Christodoulos A. Floudas; Panos M. Pardalos	2001	Springer US
Linear Programming Models for Classification	Paul A. Rubin	Encyclopedia of Optimization	Christodoulos A. Floudas; Panos M. Pardalos	2nd ed. 2009	Springer US
Linear Parameter Models for Classification		Bayesian Reasoning and Machine Learning	David Barber	2011	Cambridge University Press
Linear Programming Models for Classification		Reference Encyclopedia of Optimization		2009	Springer
Linear Parameter Models for Classification		Bayesian Reasoning and Machine Learning	David Barber
4 Linear Models for Classification		Pattern Recognition and Machine Learning (Information Science and Statistics)	Christopher M. Bishop	2006	Springer Science+Business Media, LLC
4 Linear Models for Classification		Pattern Recognition and Machine Learning	Christopher M. Bishop	2011	Springer
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