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Advanced deep learning with Keras : apply deep learning techniques, autoencoders, GANs, variational

Atienza, Rowel, author.
London, England : Packt Publishing, Limited, [2018] 2018

Application of neural networks and other learning technologies in process engineering

River Edge, NJ : ICP, 2001. 2001

The application of neural networks to the SSME startup transient

Meyer, Claudia M.
Cleveland, Ohio. : National Aeronautics and Space Administration, Lewis Research Center ; [Hanover, Md.] : Available from the NASA Center for AeroSpace Information, [1991] 1991

Approximation methods for efficient learning of Bayesian networks

Riggelsen, Carsten.
Amsterdam ; Washington, DC : IOS Press, c2008. 2008

Artificial intelligence-based design of reinforced concrete structures : artificial neural networks

Hong, Won-Kee (Professor of architectural engineering)
[S.l.] : Woodhead Publishing, 2023. 2023

Artificial intelligence in the age of neural networks and brain computing

London, United Kingdom : Academic Press, an imprint of Elsevier, [2019] 2019

Artificial intelligence in the age of neural networks and brain computing

Amsterdam : Academic Press, 2023. 2023

Artificial intelligence in the age of neural networks and brain computing

London, United Kingdom ; San Diego, CA : Academic Press ia an imprint of Elsevier, [2024] 2024

Artificial neural network for software reliability prediction

Bisi, Manjubala, author.
Hoboken, New Jersey ; Beverly, Massachusetts : John Wiley & Sons : Scrivener Publishing, 2017. 2017

Artificial neural network modeling of water and wastewater treatment processes

Khataee, Ali R. (Ali Reza), 1977-
New York : Nova Science Publishers, c2011. 2011

Artificial neural network training and software implementation techniques

Kattan, Ali.
Hauppauge, N.Y. : Nova Science Publishers, c2011. 2011

Artificial neural networks

Schalkoff, Robert J.
New York : McGraw-Hill, c1997. 1997

Artificial neural networks for engineering applications

St. Louis, Missouri : Elsevier, [2019] 2019

Artificial neural networks for renewable energy systems and real-world applications

London : Academic Press, 2022. 2022

Artificial neural systems : principle and practice

Lorrentz, Pierre, author.
Sharjah : Bentham Science Publishers Limited, [2015] 2015

Autoplan a self-processing network model for an extended blocks world planning environment

D'Autrechy, C. Lynne.
College Park, Md. : University of Maryland, [1990] 1990

Bayesian learning for neural networks

Neal, Radford M., author.
New York : Springer, [1996] 1996

Bio-inspired emergent control of locomotion systems

Frasca, Mattia.
River Edge, N.J. ; London : World Scientific, c2004. 2004

Bioinformatics the machine learning approach

Baldi, Pierre.
Cambridge, Mass. : MIT Press, c2001. 2001

Blind equalization in neural networks : theory, algorithms and applications

Berlin, [Germany] ; Boston, [Massachusetts] : De Gruyter : Tsinghua University Press, 2018. 2018

Brain-mind machinery brain-inspired computing and mind opening

Ng, G. W. (Gee Wah), 1964-
Hackensack, NJ : World Scientific, c2009. 2009

Cellular neural networks and visual computing foundation and applications

Chua, Leon O., 1936-
Cambridge, UK ; New York, NY : Cambridge University Press, 2002. 2002

Cellular neural networks, multi-scroll chaos and synchronization

Yalcin, Mustak E.
New Jersey ; London : World Scientific, c2005. 2005

Chaos, CNN, memristors and beyond a festschrift for Leon Chua

Singapore ; London : World Scientific, 2013. 2013

Cognitive science : the science of intelligent systems

Luger, George F.
San Diego : Academic Press, [1994] 1994

Cognitive systems information processing meets brain science

Amsterdam ; Boston : Elsevier Academic Press, c2006. 2006

Complex valued nonlinear adaptive filters noncircularity, widely linear, and neural models

Mandic, Danilo P.
Hoboken, N.J. : Wiley, c2009. 2009

Computational ecology artificial neural networks and their applications

Zhang, Wenjun.
Hackensack, N.J. : World Scientific, 2010. 2010

Computational neural networks for geophysical data processing

New York : Pergamon, 2001. 2001

Deep learning for computer vision : expert techniques to train advanced neural networks using Tensor

Shanmugamani, Rajalingappaa, author.
Birmingham, England : Paths International Ltd, 2018. 2018

Deep learning : principios y fundamentos

Bosch Rue, Anna, author.
Barcelona : Editorial UOC, 2020. 2020

Deep learning with Pytorch quick start guide : learn to train and deploy neural network models in Py

Julian, David, author.
Birmingham : Packt, 2018. 2018

Deterministic learning theory for identification, recognition, and control

Wang, Cong.
Boca Raton : CRC Press, c2010. 2010

Differential neural networks for robust nonlinear control identification, state estimation and traje

Poznyak, Alexander S.
Singapore ; River Edge NJ : World Scientific, c2001. 2001

Discrete-time inverse optimal control for nonlinear systems

Sanchez, Edgar N., author.
Boca Raton, Florida : CRC Press, Taylor & Francis Group, [2013] 2013

Discrete-time neural observers : analysis and applications

Alanis, Alma Y., author.
London : Academic Press, an imprint of Elsevier, [2017] 2017

Enhancement of distribution system state estimation using pruned physics-aware neural networks : pre

Tran, Minh-Quan, author.
Golden, CO : National Renewable Energy Laboratory, 2021. 2021

A first course in fuzzy logic

Nguyen, Hung T., 1944-
Boca Raton, Fla. : CRC Press, c1997. 1997

Flexible neuro-fuzzy systems structures, learning, and performance evaluation

Rutkowski, Leszek.
Boston ; London : Kluwer Academic Publishers, c2004. 2004

Focus on artificial neural networks

New York : Nova Science Publishers, c2011. 2011

Fuzzy logic and neural networks basic concepts and application

Alavala, Chennakesava R.
New Delhi : New Age International (P) Ltd., Publishers, [n.d.]  

Fuzzy neural network theory and application

Liu, Puyin.
River Edge, NJ : World Scientific, c2004. 2004

Fuzzy neural networks for real time control applications : concepts, modeling and algorithms for fas

Kayacan, Erdal, author.
Amsterdam : Butterworth-Heinemann is an imprint of Elsevier, [2015]. 2015

Generative adversarial networks for image-to-image translation

London : Academic Press, 2021. 2021

A guide to neural computing applications

Tarassenko, Lionel.
London : Arnold ; New York : Co-published in North, Central, and South America by John Wiley, ©1998. 1998

Handbook of neural computation

Amsterdam : Academic Press, 2017. 2017

Hands-on generative adversarial networks with Keras : your guide to implementing next-generation gen

Valle, Rafael, author.
Birmingham ; Mumbai : Packt Publishing Ltd, 2019. 2019

Hybrid methods in pattern recognition

River Edge, N.J. : World Scientific, c2002. 2002

Identifying Outputs of Generative Adversarial Networks Act : report of the Committee on Commerce, Sc

United States. Congress. Senate. Committee on Commerce, Science, and Transportation, author.
Washington : U.S. Government Publishing Office, 2020. 2020

Information processing by biochemical systems neural network-type configurations

Filo, Orna.
Hoboken, NJ : John Wiley & Sons, c2010. 2010