Download or read book The Roots of Backpropagation written by Paul John Werbos and published by John Wiley & Sons. This book was released on 1994-03-31 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Backpropagation written by Yves Chauvin and published by Psychology Press. This book was released on 2013-02-01 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book System Theory and Practical Applications of Biomedical Signals written by Gail D. Baura and published by John Wiley & Sons. This book was released on 2002-08-26 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: System theory is becoming increasingly important to medical applications. Yet, biomedical and digital signal processing researchers rarely have expertise in practical medical applications, and medical instrumentation designers usually are unfamiliar with system theory. System Theory and Practical Applications for Biomedical Signals bridges those gaps in a practical manner, showing how various aspects of system theory are put into practice by industry. The chapters are intentionally organized in groups of two chapters, with the first chapter describing a system theory technology, and the second chapter describing an industrial application of this technology. Each theory chapter contains a general overview of a system theory technology, which is intended as background material for the application chapter. Each application chapter contains a history of a highlighted medical instrument, summary of appropriate physiology, discussion of the problem of interest and previous empirical solutions, and review of a solution that utilizes the theory in the previous chapter. Biomedical and DSP academic researchers pursuing grants and industry funding will find its real-world approach extremely valuable. Its in-depth discussion of the theoretical issues will clarify for medical instrumentation managers how system theory can compensate for less-than-ideal sensors. With application MATLAB® exercises and suggestions for system theory course work included, the text also fills the need for detailed information for students or practicing engineers interested in instrument design. An Instructor Support FTP site is available from the Wiley editorial department: ftp://ftp.ieee.org/uploads/press/baura
Download or read book Introduction to Neural and Cognitive Modeling written by Daniel S. Levine and published by Routledge. This book was released on 2018-10-26 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a general introduction to the field of neural networks. Thoroughly revised and updated from the previous editions of 1991 and 2000, the current edition concentrates on networks for modeling brain processes involved in cognitive and behavioral functions. Part one explores the philosophy of modeling and the field’s history starting from the mid-1940s, and then discusses past models of associative learning and of short-term memory that provide building blocks for more complex recent models. Part two of the book reviews recent experimental findings in cognitive neuroscience and discusses models of conditioning, categorization, category learning, vision, visual attention, sequence learning, behavioral control, decision making, reasoning, and creativity. The book presents these models both as abstract ideas and through examples and concrete data for specific brain regions. The book includes two appendices to help ground the reader: one reviewing the mathematics used in network modeling, and a second reviewing basic neuroscience at both the neuron and brain region level. The book also includes equations, practice exercises, and thought experiments.
Download or read book Optimization and Learning written by Bernabé Dorronsoro and published by Springer Nature. This book was released on 2020-02-15 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the Third International Conference on Optimization and Learning, OLA 2020, held in Cádiz, Spain, in February 2020. The 23 full papers were carefully reviewed and selected from 55 submissions. The papers presented in the volume focus on the future challenges of optimization and learning methods, identifying and exploiting their synergies,and analyzing their applications in different fields, such as health, industry 4.0, games, logistics, etc.
Download or read book Neural Networks written by G David Garson and published by SAGE. This book was released on 1998-09-24 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the first accessible introduction to neural network analysis as a methodological strategy for social scientists. The author details numerous studies and examples which illustrate the advantages of neural network analysis over other quantitative and modelling methods in widespread use. Methods are presented in an accessible style for readers who do not have a background in computer science. The book provides a history of neural network methods, a substantial review of the literature, detailed applications, coverage of the most common alternative models and examples of two leading software packages for neural network analysis.
Download or read book Neural Networks in Chemical Reaction Dynamics written by Lionel Raff and published by OUP USA. This book was released on 2012-01-18 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph presents recent advances in neural network (NN) approaches and applications to chemical reaction dynamics. Topics covered include: (i) the development of ab initio potential-energy surfaces (PES) for complex multichannel systems using modified novelty sampling and feedforward NNs; (ii) methods for sampling the configuration space of critical importance, such as trajectory and novelty sampling methods and gradient fitting methods; (iii) parametrization of interatomic potential functions using a genetic algorithm accelerated with a NN; (iv) parametrization of analytic interatomic potential functions using NNs; (v) self-starting methods for obtaining analytic PES from ab inito electronic structure calculations using direct dynamics; (vi) development of a novel method, namely, combined function derivative approximation (CFDA) for simultaneous fitting of a PES and its corresponding force fields using feedforward neural networks; (vii) development of generalized PES using many-body expansions, NNs, and moiety energy approximations; (viii) NN methods for data analysis, reaction probabilities, and statistical error reduction in chemical reaction dynamics; (ix) accurate prediction of higher-level electronic structure energies (e.g. MP4 or higher) for large databases using NNs, lower-level (Hartree-Fock) energies, and small subsets of the higher-energy database; and finally (x) illustrative examples of NN applications to chemical reaction dynamics of increasing complexity starting from simple near equilibrium structures (vibrational state studies) to more complex non-adiabatic reactions. The monograph is prepared by an interdisciplinary group of researchers working as a team for nearly two decades at Oklahoma State University, Stillwater, OK with expertise in gas phase reaction dynamics; neural networks; various aspects of MD and Monte Carlo (MC) simulations of nanometric cutting, tribology, and material properties at nanoscale; scaling laws from atomistic to continuum; and neural networks applications to chemical reaction dynamics. It is anticipated that this emerging field of NN in chemical reaction dynamics will play an increasingly important role in MD, MC, and quantum mechanical studies in the years to come.
Download or read book Deep Learning with TensorFlow 2 and Keras written by Antonio Gulli and published by Packt Publishing Ltd. This book was released on 2019-12-27 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Key FeaturesIntroduces and then uses TensorFlow 2 and Keras right from the startTeaches key machine and deep learning techniquesUnderstand the fundamentals of deep learning and machine learning through clear explanations and extensive code samplesBook Description Deep Learning with TensorFlow 2 and Keras, Second Edition teaches neural networks and deep learning techniques alongside TensorFlow (TF) and Keras. You’ll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow is the machine learning library of choice for professional applications, while Keras offers a simple and powerful Python API for accessing TensorFlow. TensorFlow 2 provides full Keras integration, making advanced machine learning easier and more convenient than ever before. This book also introduces neural networks with TensorFlow, runs through the main applications (regression, ConvNets (CNNs), GANs, RNNs, NLP), covers two working example apps, and then dives into TF in production, TF mobile, and using TensorFlow with AutoML. What you will learnBuild machine learning and deep learning systems with TensorFlow 2 and the Keras APIUse Regression analysis, the most popular approach to machine learningUnderstand ConvNets (convolutional neural networks) and how they are essential for deep learning systems such as image classifiersUse GANs (generative adversarial networks) to create new data that fits with existing patternsDiscover RNNs (recurrent neural networks) that can process sequences of input intelligently, using one part of a sequence to correctly interpret anotherApply deep learning to natural human language and interpret natural language texts to produce an appropriate responseTrain your models on the cloud and put TF to work in real environmentsExplore how Google tools can automate simple ML workflows without the need for complex modelingWho this book is for This book is for Python developers and data scientists who want to build machine learning and deep learning systems with TensorFlow. This book gives you the theory and practice required to use Keras, TensorFlow 2, and AutoML to build machine learning systems. Some knowledge of machine learning is expected.
Download or read book Handbook of Research on Modeling Analysis and Application of Nature Inspired Metaheuristic Algorithms written by Dash, Sujata and published by IGI Global. This book was released on 2017-08-10 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: The digital age is ripe with emerging advances and applications in technological innovations. Mimicking the structure of complex systems in nature can provide new ideas on how to organize mechanical and personal systems. The Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms is an essential scholarly resource on current algorithms that have been inspired by the natural world. Featuring coverage on diverse topics such as cellular automata, simulated annealing, genetic programming, and differential evolution, this reference publication is ideal for scientists, biological engineers, academics, students, and researchers that are interested in discovering what models from nature influence the current technology-centric world.
Download or read book World Congress on Neural Networks San Diego written by and published by Psychology Press. This book was released on 1994 with total page 916 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book World Congress on Neural Networks written by Paul Werbos and published by Routledge. This book was released on 2021-09-10 with total page 916 pages. Available in PDF, EPUB and Kindle. Book excerpt: Centered around 20 major topic areas of both theoretical and practical importance, the World Congress on Neural Networks provides its registrants -- from a diverse background encompassing industry, academia, and government -- with the latest research and applications in the neural network field.
Download or read book Learning As Self organization written by Karl H. Pribram and published by Psychology Press. This book was released on 2013-06-17 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: A year before his death, B.F. Skinner wrote that "There are two unavoidable gaps in any behavioral account: one between the stimulating action of the environment and the response of the organism and one between consequences and the resulting change in behavior. Only brain science can fill those gaps. In doing so, it completes the account; it does not give a different account of the same thing." This declaration ended the epoch of radical behaviorism to the extent that it was based on the doctrine of the "empty organism," the doctrine that a behavioral science must be constructed purely on its own level of investigation. However, Skinner was not completely correct in his assessment. Brain science on its own can no more fill the gaps than can single level behavioral science. It is the relation between data and formulations developed in the brain and the behavioral sciences that is needed. This volume is the result of The Fourth Appalachian Conference on Behavioral Neurodynamics, the first three of which were aimed at filling Skinner's first gap. Taking the series in a new direction, the aim of the fourth and subsequent conferences is to explore the second of the gaps in the behavioral account noted by Skinner. The aim of this conference was to explore the aphorism: The motivation for learning is self organization. In keeping with this aim and in the spirit of previous events, this conference's mission was to acquaint scientists working in one discipline with the work going on in other disciplines that is relevant to both. As a result, it brought together those who are making advances on the behavioral level -- mainly working in the tradition of operant conditioning -- and those working with brains -- mainly amygdala, hippocampus, and far frontal cortex.
Download or read book Fluids and Waves written by Fernanda Botelho and published by American Mathematical Soc.. This book was released on 2007 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains a series of articles on wave phenomena and fluid dynamics, highlighting recent advances in these two areas of mathematics. The collection is based on lectures presented at the conference Fluids and Waves--Recent Trends in Applied Analysis and features a rich spectrum of mathematical techniques in analysis and applications to engineering, neuroscience, physics, and biology. The mathematical topics discussed range from partial differential equations, dynamical systems and stochastic processes, to areas of classical analysis. This volume is intended as an introduction to major topics of interest and state-of-the-art analytical research in wave motion and fluid flows.
Download or read book Smart Sensors for Industry 4 0 written by Brojo Kishore Mishra and published by John Wiley & Sons. This book was released on 2024-09-04 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the essential guide to harnessing the power of cutting-edge smart sensors in Industry 4.0, offering deep insights into fundamentals, fabrication techniques, and real-world IIoT applications, equipping you with the knowledge to revolutionize your industrial processes and stay ahead in the digital era. Over the last decade, technologies like the Internet of Things (IoT), big data, cloud computing, blockchain, artificial intelligence (AI), machine learning, device automation, smart sensors, etc., have become highly developed fundamental supports of Industry 4.0, replacing the conventional production systems with advanced methods, and thereby endorsing the smart industry vision. Industry 4.0 is more flexible and agile in dealing with several risk factors, further enabling improved productivity and efficiency, distribution, increased profitability, data integrity, and enhancing customer experience in the current commercial environment. For understanding and analyzing the environment, sensors play a major role in performing the measurements based on computation-produced results from the surrounding environment. Sensors have a wide range of applications for smart industrial operations. The evolution of flexible, low-cost, and multipurpose sensors and their system integration has been examined to develop advanced devices with applications in numerous fields of technology. With the development of both the Internet of Things (IoT) and the Industrial IoT (IIoT), advanced sensors and their associated applications are developing, resulting in the necessity for IoT sensors to be used for several industrial applications. Beneficial aspects of this book include: The latest research in materials and methodology for the fabrication of intelligent sensors, its IoT system integration, and IIoT applications are brought together; Promotes a vision towards making sensor-based monitoring and control of smart industry; Recent advances and challenges of smart sensors are discussed with an emphasis on unmet challenges and future directions of a roadmap to Industry 4.0. Audience This book is highly recommended to a wide range of researchers and industry engineers working in the area of fabrication and integration of industrial smart sensors for IIoT applications, advanced materials for sensor technology, fabrication and characterization of IoT sensors, development of low-cost sensors, sensor system design and integration, and its industrial applications. Post-graduate students from different streams like computer science, electronics and electrical engineering, information technology, electronic communication, etc. will benefit from reading this book.
Download or read book Recurrent Neural Networks written by Larry Medsker and published by CRC Press. This book was released on 1999-12-20 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: With existent uses ranging from motion detection to music synthesis to financial forecasting, recurrent neural networks have generated widespread attention. The tremendous interest in these networks drives Recurrent Neural Networks: Design and Applications, a summary of the design, applications, current research, and challenges of this subfield of artificial neural networks. This overview incorporates every aspect of recurrent neural networks. It outlines the wide variety of complex learning techniques and associated research projects. Each chapter addresses architectures, from fully connected to partially connected, including recurrent multilayer feedforward. It presents problems involving trajectories, control systems, and robotics, as well as RNN use in chaotic systems. The authors also share their expert knowledge of ideas for alternate designs and advances in theoretical aspects. The dynamical behavior of recurrent neural networks is useful for solving problems in science, engineering, and business. This approach will yield huge advances in the coming years. Recurrent Neural Networks illuminates the opportunities and provides you with a broad view of the current events in this rich field.
Download or read book Computational Learning Approaches to Data Analytics in Biomedical Applications written by Khalid Al-Jabery and published by Academic Press. This book was released on 2019-11-20 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis using varied machine learning and statistical techniques. It presents insights on biomedical data processing, innovative clustering algorithms and techniques, and connections between statistical analysis and clustering. The book introduces and discusses the major problems relating to data analytics, provides a review of influential and state-of-the-art learning algorithms for biomedical applications, reviews cluster validity indices and how to select the appropriate index, and includes an overview of statistical methods that can be applied to increase confidence in the clustering framework and analysis of the results obtained. Includes an overview of data analytics in biomedical applications and current challenges Updates on the latest research in supervised learning algorithms and applications, clustering algorithms and cluster validation indices Provides complete coverage of computational and statistical analysis tools for biomedical data analysis Presents hands-on training on the use of Python libraries, MATLAB® tools, WEKA, SAP-HANA and R/Bioconductor
Download or read book The 8th International Conference on Robotic Vision Signal Processing Power Applications written by Harsa Amylia Mat Sakim and published by Springer. This book was released on 2014-07-08 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceeding is a collection of research papers presented, at the 8th International Conference on Robotics, Vision, Signal Processing and Power Applications (ROVISP 2013), by researchers, scientists, engineers, academicians as well as industrial professionals from all around the globe. The topics of interest are as follows but are not limited to: • Robotics, Control, Mechatronics and Automation • Vision, Image, and Signal Processing • Artificial Intelligence and Computer Applications • Electronic Design and Applications • Telecommunication Systems and Applications • Power System and Industrial Applications
