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Backpropagation

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Backpropagation

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Author : Yves Chauvin
language : en
Publisher: Psychology Press
Release Date : 2013-02-01

Backpropagation written by Yves Chauvin and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-02-01 with Psychology categories.

Composed of three sections, this book presents the most popular training algorithm for neural networks: backpropagation. The first section presents the theory and principles behind backpropagation as seen from different perspectives such as statistics, machine learning, and dynamical systems. The second presents a number of network architectures that may be designed to match the general concepts of Parallel Distributed Processing with backpropagation learning. Finally, the third section shows how these principles can be applied to a number of different fields related to the cognitive sciences, including control, speech recognition, robotics, image processing, and cognitive psychology. The volume is designed to provide both a solid theoretical foundation and a set of examples that show the versatility of the concepts. Useful to experts in the field, it should also be most helpful to students seeking to understand the basic principles of connectionist learning and to engineers wanting to add neural networks in general -- and backpropagation in particular -- to their set of problem-solving methods.

The Roots Of Backpropagation

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Author : Paul John Werbos
language : en
Publisher: John Wiley & Sons
Release Date : 1994-03-31

The Roots Of Backpropagation written by Paul John Werbos and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-03-31 with Computers categories.

Now, for the first time, publication of the landmark work inbackpropagation! Scientists, engineers, statisticians, operationsresearchers, and other investigators involved in neural networkshave long sought direct access to Paul Werbos's groundbreaking,much-cited 1974 Harvard doctoral thesis, The Roots ofBackpropagation, which laid the foundation of backpropagation. Now,with the publication of its full text, these practitioners can gostraight to the original material and gain a deeper, practicalunderstanding of this unique mathematical approach to socialstudies and related fields. In addition, Werbos has provided threemore recent research papers, which were inspired by his originalwork, and a new guide to the field. Originally written for readerswho lacked any knowledge of neural nets, The Roots ofBackpropagation firmly established both its historical andcontinuing significance as it: * Demonstrates the ongoing value and new potential ofbackpropagation * Creates a wealth of sound mathematical tools useful acrossdisciplines * Sets the stage for the emerging area of fast automaticdifferentiation * Describes new designs for forecasting and control which exploitbackpropagation * Unifies concepts from Freud, Jung, biologists, and others into anew mathematical picture of the human mind and how it works * Certifies the viability of Deutsch's model of nationalism as apredictive tool--as well as the utility of extensions of thiscentral paradigm "What a delight it was to see Paul Werbos rediscover Freud'sversion of 'back-propagation.' Freud was adamant (in The Projectfor a Scientific Psychology) that selective learning could onlytake place if the presynaptic neuron was as influenced as is thepostsynaptic neuron during excitation. Such activation of bothsides of the contact barrier (Freud's name for the synapse) wasaccomplished by reducing synaptic resistance by the absorption of'energy' at the synaptic membranes. Not bad for 1895! But Werbos1993 is even better." --Karl H. Pribram Professor Emeritus,Stanford University

Backpropagation

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Author : Yves Chauvin (Ph. D.)
language : en
Publisher: Psychology Press
Release Date : 1995

Backpropagation written by Yves Chauvin (Ph. D.) and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Computers categories.

Neural Network Control Of Robot Manipulators And Non Linear Systems

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Author : F W Lewis
language : en
Publisher: CRC Press
Release Date : 2020-08-13

Neural Network Control Of Robot Manipulators And Non Linear Systems written by F W Lewis and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-13 with Technology & Engineering categories.

There has been great interest in "universal controllers" that mimic the functions of human processes to learn about the systems they are controlling on-line so that performance improves automatically. Neural network controllers are derived for robot manipulators in a variety of applications including position control, force control, link flexibility stabilization and the management of high-frequency joint and motor dynamics. The first chapter provides a background on neural networks and the second on dynamical systems and control. Chapter three introduces the robot control problem and standard techniques such as torque, adaptive and robust control. Subsequent chapters give design techniques and Stability Proofs For NN Controllers For Robot Arms, Practical Robotic systems with high frequency vibratory modes, force control and a general class of non-linear systems. The last chapters are devoted to discrete- time NN controllers. Throughout the text, worked examples are provided.

Biological And Biomedical Infrared Spectroscopy

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Author : Andreas Barth
language : en
Publisher: IOS Press
Release Date : 2009

Biological And Biomedical Infrared Spectroscopy written by Andreas Barth and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Science categories.

Although infrared spectroscopy has been applied with success to the study of important biological and biomedical processes for many years, key advances in this vibrant technique have led to its increasing use, ranging from characterization of individual macromolecules (DNA, RNA, lipids, proteins) to human tissues, cells and their components. Infrared spectroscopy thus has a significant role to play in the analysis of the vast number of genes and proteins being identified by the various genomic sequencing projects. Whilst this book gives an overview of the field, it highlights more recent developments, such as the use of bright synchrotron radiation for recording infrared spectra, the development of two-dimensional infrared spectroscopy and the ability to record infrared spectra at ultra fast speeds.

Machine Learning Based Modelling In Atomic Layer Deposition Processes

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Author : Oluwatobi Adeleke
language : en
Publisher: CRC Press
Release Date : 2023-12-15

Machine Learning Based Modelling In Atomic Layer Deposition Processes written by Oluwatobi Adeleke and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-15 with Technology & Engineering categories.

While thin film technology has benefited greatly from artificial intelligence (AI) and machine learning (ML) techniques, there is still much to be learned from a full-scale exploration of these technologies in atomic layer deposition (ALD). This book provides in-depth information regarding the application of ML-based modeling techniques in thin film technology as a standalone approach and integrated with the classical simulation and modeling methods. It is the first of its kind to present detailed information regarding approaches in ML-based modeling, optimization, and prediction of the behaviors and characteristics of ALD for improved process quality control and discovery of new materials. As such, this book fills significant knowledge gaps in the existing resources as it provides extensive information on ML and its applications in film thin technology. Offers an in-depth overview of the fundamentals of thin film technology, state-of-the-art computational simulation approaches in ALD, ML techniques, algorithms, applications, and challenges. Establishes the need for and significance of ML applications in ALD while introducing integration approaches for ML techniques with computation simulation approaches. Explores the application of key techniques in ML, such as predictive analysis, classification techniques, feature engineering, image processing capability, and microstructural analysis of deep learning algorithms and generative model benefits in ALD. Helps readers gain a holistic understanding of the exciting applications of ML-based solutions to ALD problems and apply them to real-world issues. Aimed at materials scientists and engineers, this book fills significant knowledge gaps in existing resources as it provides extensive information on ML and its applications in film thin technology. It also opens space for future intensive research and intriguing opportunities for ML-enhanced ALD processes, which scale from academic to industrial applications.

Handbook Of Machine Learning For Computational Optimization

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Author : Vishal Jain
language : en
Publisher: CRC Press
Release Date : 2021-11-02

Handbook Of Machine Learning For Computational Optimization written by Vishal Jain and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-02 with Business & Economics categories.

Technology is moving at an exponential pace in this era of computational intelligence. Machine learning has emerged as one of the most promising tools used to challenge and think beyond current limitations. This handbook will provide readers with a leading edge to improving their products and processes through optimal and smarter machine learning techniques. This handbook focuses on new machine learning developments that can lead to newly developed applications. It uses a predictive and futuristic approach, which makes machine learning a promising tool for processes and sustainable solutions. It also promotes newer algorithms that are more efficient and reliable for new dimensions in discovering other applications, and then goes on to discuss the potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making. Individuals looking for machine learning-based knowledge will find interest in this handbook. The readership ranges from undergraduate students of engineering and allied courses to researchers, professionals, and application designers.

Artificial Neural Networks Icann 2007

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Author : Joaquim Marques de Sá
language : en
Publisher: Springer
Release Date : 2007-09-14

Artificial Neural Networks Icann 2007 written by Joaquim Marques de Sá and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09-14 with Computers categories.

This book is the first of a two-volume set that constitutes the refereed proceedings of the 17th International Conference on Artificial Neural Networks, ICANN 2007, held in Porto, Portugal, September 2007. Coverage includes advances in neural network learning methods, advances in neural network architectures, neural dynamics and complex systems, data analysis, evolutionary computing, agents learning, as well as temporal synchronization and nonlinear dynamics in neural networks.

Icann 93

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Author : Stan Gielen
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Icann 93 written by Stan Gielen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.

This book contains the proceedings of the International Confer ence on Artificial Neural Networks which was held between September 13 and 16 in Amsterdam. It is the third in a series which started two years ago in Helsinki and which last year took place in Brighton. Thanks to the European Neural Network Society, ICANN has emerged as the leading conference on neural networks in Europe. Neural networks is a field of research which has enjoyed a rapid expansion and great popularity in both the academic and industrial research communities. The field is motivated by the commonly held belief that applications in the fields of artificial intelligence and robotics will benefit from a good understanding of the neural information processing properties that underlie human intelligence. Essential aspects of neural information processing are highly parallel execution of com putation, integration of memory and process, and robustness against fluctuations. It is believed that intelligent skills, such as perception, motion and cognition, can be easier realized in neuro-computers than in a conventional computing paradigm. This requires active research in neurobiology to extract com putational principles from experimental neurobiological find ings, in physics and mathematics to study the relation between architecture and function in neural networks, and in cognitive science to study higher brain functions, such as language and reasoning. Neural networks technology has already lead to practical methods that solve real problems in a wide area of industrial applications. The clusters on robotics and applications contain sessions on various sub-topics in these fields.

From Natural To Artificial Neural Computation

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Author : Jose Mira
language : en
Publisher: Springer Science & Business Media
Release Date : 1995-05-24

From Natural To Artificial Neural Computation written by Jose Mira and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-05-24 with Computers categories.

This volume presents the proceedings of the International Workshop on Artificial Neural Networks, IWANN '95, held in Torremolinos near Malaga, Spain in June 1995. The book contains 143 revised papers selected from a wealth of submissions and five invited contributions; it covers all current aspects of neural computation and presents the state of the art of ANN research and applications. The papers are organized in sections on neuroscience, computational models of neurons and neural nets, organization principles, learning, cognitive science and AI, neurosimulators, implementation, neural networks for perception, and neural networks for communication and control.

Backpropagation

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