"AppART: An ART Hybrid Stable Learning Neural Network for Universal Function Approximation"

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Book	Author(s)	Year	Publisher
Stable Adaptive Neural Network Control	S.S. Ge; C.C. Hang; T.H. Lee; Tao Zhang	2002	Springer US
Hybrid Neural Network and Expert Systems	Larry R. Medsker	1994	Springer US
Neural Network Learning: Theoretical Foundations	Martin Anthony; Peter L. Bartlett	1999-11	Cambridge University Press
Intelligent Systems II: Complete Approximation by Neural Network Operators	George A. Anastassiou	2016	Springer International Publishing
Neural Network Learning and Expert Systems	Stephen I. Gallant	1993	MIT Press
Neural Network Learning and Expert Systems	Stephen I. Gallant	1993	MIT Press,
Neural network learning and expert systems	Stephen I. Gallant	1993	MIT Press
Explanation-Based Neural Network Learning: A Lifelong Learning Approach	Sebastian Thrun	1996	Springer US
Neural Network Models: An Analysis	Philippe de Wilde	1996	Springer Berlin Heidelberg
Hybrid Neural Systems	Stefan Wermter; Ron Sun	2000	Springer Berlin Heidelberg
Reinforcement Learning with Hybrid Quantum Approximation in the NISQ Context	Leonhard Kunczik	1st ed. 2022	Springer Fachmedien Wiesbaden
Neural Network Design and the Complexity of Learning	J. Stephen Judd	1990	MIT Press
Neural Network Design and the Complexity of Learning	J. Stephen Judd	1990	MIT Press,
Animal learning and cognition: a neural network approach /	Schmajuk, Nestor A.	1997.	Cambridge University Press,
Modular learning in neural networks: a modularized approach to neural network classification	Tomas Hrycej	1992	Wiley
An Introduction to Neural Network Methods for Differential Equations	Neha Yadav; Anupam Yadav; Manoj Kumar	2015	Springer Netherlands
Neural network principles /	Harvey, Robert L.	1994.	Prentice Hall,
A neural network test for heteroskedasticity	Mark Kamstra	1991	Simon Fraser University
Learning Theory: An Approximation Theory Viewpoint	Felipe Cucker; Ding Xuan Zhou	2007-03	Cambridge University Press
Neural, novel & hybrid algorithms for time series prediction /	Masters, Timothy.	[1995], ©1995.	John Wiley & Sons,
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
AppART: An ART Hybrid Stable Learning Neural Network for Universal Function Approximation	Luis Martí; Alberto Policriti; Luciano García	Hybrid Information Systems	Ajith Abraham; Mario Köppen	2002	Physica-Verlag HD
AppART: a Hybrid Neural Network Based on Adaptive Resonance Theory for Universal Function Approximation	Luis Martí; Alberto Policriti; Luciano García	Innovations in Intelligent Systems	Ajith Abraham; Berend Jan van der Zwaag	2004	Springer Berlin Heidelberg
Developing Q-learning with neural network function approximation		PyTorch 1. x Reinforcement Learning Cookbook: Over 60 recipes to design, develop, and deploy self-learning AI models using Python	Yuxi (Hayden) Liu	2019	Packt Publishing
Wavelets Based Neural Network for Function Approximation	Yong Fang; Tommy W. S. Chow	Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Chengdu, China, May 28 - June 1, 2006, Proceedings, Part I	Jun Wang; Zhang Yi; Jacek M. Zurada; Bao-Liang Lu; Yin Hujun	2006	Springer Berlin Heidelberg
Function approximation using a neural network		Mastering Reinforcement Learning with Python: Build next-generation, self-learning models using reinforcement learning techniques and best practices	Enes Bilgin	2020	Packt Publishing
Artificial Neural Network for Approximation		Nonlinear and Distributed Circuits	Wai-Kai Chen	2005	CRC Press
Arctangent Function Based Abstract Neural Network Approximation	George A. Anastassiou	Intelligent Computations: Abstract Fractional Calculus, Inequalities, Approximations	George A. Anastassiou	1st ed. 2018	Springer International Publishing
A Fast Nonseparable Wavelet Neural Network for Function Approximation	Jun Zhang; Xieping Gao; Chunhong Cao; Fen Xiao	Advances in Natural Computation: First International Conference, ICNC 2005, Changsha, China, August 27-29, 2005, Proceedings, Part I	Lipo Wang; Ke Chen; Yew Soon Ong	2005	Springer Berlin Heidelberg
522 Hybrid function approximation		GMDH - Methodology and Implementation in C	Godfrey Onwubolu	2014	World Scientific Publishing Company Incorporated
An Active Learning Based Hybrid Neural Network for Joint Information Extraction	Yan Zhuang; Guoliang Li; Wanguo Xue; Fu Zhu	Web Information Systems Engineering – WISE 2020: 21st International Conference, Amsterdam, The Netherlands, October 20–24, 2020, Proceedings, Part II	Zhisheng Huang; Wouter Beek; Hua Wang; Rui Zhou; Yanchun Zhang	1st ed. 2020	Springer International Publishing
Hybrid Optimization Scheme for Radial Basis Function Neural Network	Vidyut Dey; Dilip Kumar Pratihar; Gauranga Lal Datta	Simulated Evolution and Learning: 8th International Conference, SEAL 2010, Kanpur, India, December 1-4, 2010, Proceedings	Kalyanmoy Deb; Arnab Bhattacharya; Nirupam Chakraborti; Partha Chakroborty; Swagatam Das; Joydeep Dutta; Santosh K. Gupta; Ashu Jain; Varun Aggarwal; Juergen Branke; Sushil J. Louis; Kay Chen Tan	2010	Springer Berlin Heidelberg
Approximation Neural Network for Phoneme Synthesis	Marius Crisan	Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014: Volume 1	Suresh Chandra Satapathy; Bhabendra Narayan Biswal; Siba K. Udgata; J.K. Mandal	2015	Springer International Publishing
Modern Neural Methods for Function Approximation	Iuliana F. Iatan	Issues in the Use of Neural Networks in Information Retrieval	Iuliana F. Iatan	1st ed. 2017	Springer International Publishing
Online Learning Neural Network for Adaptively Weighted Hybrid Modeling	Shao-Ming Yang; Ya-Lin Wang; Yong-fei Xue; Bei Sun; Bu-song Yang	Neural Information Processing: 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part II	Akira Hirose; Seiichi Ozawa; Kenji Doya; Kazushi Ikeda; Minho Lee; Derong Liu	1st ed. 2016	Springer International Publishing
Multivariate Error Function Based Neural Network Operators Approximation	George A. Anastassiou	Intelligent Systems II: Complete Approximation by Neural Network Operators	George A. Anastassiou	2016	Springer International Publishing
72 Value function approximation and critic neural network		Optimal Adaptive Control and Differential Games by Reinforcement Learning Principles	Draguna Vrabie, Kyriakos G. Vamvoudakis, Frank. L Lewis	2013	The Institution of Engineering and Technology
931 Value function approximation and critic neural network		Optimal Adaptive Control and Differential Games by Reinforcement Learning Principles	Draguna Vrabie, Kyriakos G. Vamvoudakis, Frank. L Lewis	2013	The Institution of Engineering and Technology
ADFUNN: An Adaptive Function Neural Network	Dominic Palmer-Brown; Miao Kang	Adaptive and Natural Computing Algorithms: Proceedings of the International Conference in Coimbra, Portugal, 2005	Bernardete Ribeiro; Rudolf F. Albrecht; Andrej Dobnikar; David W. Pearson; Nigel C. Steele	2005	Springer Vienna
Neural Network Assistants for Learning	Joseph Psotka	Encyclopedia of the Sciences of Learning	Norbert M. Seel	2012	Springer US
Hybridization of Metaheuristic and Population-Based Algorithms with Neural Network Learning for Function Approximation	Zhen-Yao Chen	Advances in Computational Collective Intelligence: 13th International Conference, ICCCI 2021, Kallithea, Rhodes, Greece, September 29 – October 1, 2021, Proceedings	Krystian Wojtkiewicz; Jan Treur; Elias Pimenidis; Marcin Maleszka	1st ed. 2021	Springer International Publishing
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