From Natural To Artificial Neural Computation

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From Natural to Artificial Neural Computation

Author : Jose Mira
Publisher : Springer Science & Business Media
ISBN 13 : 9783540594970
Total Pages : 1182 pages
Book Rating : 4.5/5 (949 download)

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Book Synopsis From Natural to Artificial Neural Computation by : Jose Mira

Download or read book From Natural to Artificial Neural Computation written by Jose Mira and published by Springer Science & Business Media. This book was released on 1995-05-24 with total page 1182 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Handbook of Neural Computation

Author : Pijush Samui
Publisher : Academic Press
ISBN 13 : 0128113197
Total Pages : 660 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Handbook of Neural Computation by : Pijush Samui

Download or read book Handbook of Neural Computation written by Pijush Samui and published by Academic Press. This book was released on 2017-07-18 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations, such as data prediction, classification of images, analysis of big data, and intelligent decision-making, this book provides readers with the latest, cutting-edge research in one comprehensive text. - Features high-quality research articles on multivariate adaptive regression splines, the minimax probability machine, and more - Discusses machine learning techniques, including classification, clustering, regression, web mining, information retrieval and natural language processing - Covers supervised, unsupervised, reinforced, ensemble, and nature-inspired learning methods

Unsupervised Learning

Author : Geoffrey Hinton
Publisher : MIT Press
ISBN 13 : 9780262581684
Total Pages : 420 pages
Book Rating : 4.5/5 (816 download)

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Book Synopsis Unsupervised Learning by : Geoffrey Hinton

Download or read book Unsupervised Learning written by Geoffrey Hinton and published by MIT Press. This book was released on 1999-05-24 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. This volume of Foundations of Neural Computation, on unsupervised learning algorithms, focuses on neural network learning algorithms that do not require an explicit teacher. The goal of unsupervised learning is to extract an efficient internal representation of the statistical structure implicit in the inputs. These algorithms provide insights into the development of the cerebral cortex and implicit learning in humans. They are also of interest to engineers working in areas such as computer vision and speech recognition who seek efficient representations of raw input data.

Artificial Intelligence in the Age of Neural Networks and Brain Computing

Author : Robert Kozma
Publisher : Academic Press
ISBN 13 : 0323958168
Total Pages : 398 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Artificial Intelligence in the Age of Neural Networks and Brain Computing by : Robert Kozma

Download or read book Artificial Intelligence in the Age of Neural Networks and Brain Computing written by Robert Kozma and published by Academic Press. This book was released on 2023-10-11 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. The book covers the major basic ideas of "brain-like computing" behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters. - Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN - Authored by top experts, global field pioneers, and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making - Edited by high-level academics and researchers in intelligent systems and neural networks - Includes all new chapters, including topics such as Frontiers in Recurrent Neural Network Research; Big Science, Team Science, Open Science for Neuroscience; A Model-Based Approach for Bridging Scales of Cortical Activity; A Cognitive Architecture for Object Recognition in Video; How Brain Architecture Leads to Abstract Thought; Deep Learning-Based Speech Separation and Advances in AI, Neural Networks

Sensitivity Analysis for Neural Networks

Author : Daniel S. Yeung
Publisher : Springer Science & Business Media
ISBN 13 : 3642025323
Total Pages : 89 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Sensitivity Analysis for Neural Networks by : Daniel S. Yeung

Download or read book Sensitivity Analysis for Neural Networks written by Daniel S. Yeung and published by Springer Science & Business Media. This book was released on 2009-11-09 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks are used to model systems that receive inputs and produce outputs. The relationships between the inputs and outputs and the representation parameters are critical issues in the design of related engineering systems, and sensitivity analysis concerns methods for analyzing these relationships. Perturbations of neural networks are caused by machine imprecision, and they can be simulated by embedding disturbances in the original inputs or connection weights, allowing us to study the characteristics of a function under small perturbations of its parameters. This is the first book to present a systematic description of sensitivity analysis methods for artificial neural networks. It covers sensitivity analysis of multilayer perceptron neural networks and radial basis function neural networks, two widely used models in the machine learning field. The authors examine the applications of such analysis in tasks such as feature selection, sample reduction, and network optimization. The book will be useful for engineers applying neural network sensitivity analysis to solve practical problems, and for researchers interested in foundational problems in neural networks.

Handbook of Neural Computation

Author : E Fiesler
Publisher : CRC Press
ISBN 13 : 1420050648
Total Pages : 1094 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Handbook of Neural Computation by : E Fiesler

Download or read book Handbook of Neural Computation written by E Fiesler and published by CRC Press. This book was released on 2020-01-15 with total page 1094 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Neural Computation is a practical, hands-on guide to the design and implementation of neural networks used by scientists and engineers to tackle difficult and/or time-consuming problems. The handbook bridges an information pathway between scientists and engineers in different disciplines who apply neural networks to similar probl

Neural Computing for Advanced Applications

Author : Haijun Zhang
Publisher : Springer Nature
ISBN 13 : 981157670X
Total Pages : 542 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Neural Computing for Advanced Applications by : Haijun Zhang

Download or read book Neural Computing for Advanced Applications written by Haijun Zhang and published by Springer Nature. This book was released on 2020-08-12 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents refereed proceedings of the First International Conference on Neural Computing for Advanced Applications, NCAA 2020, held in July, 2020. Due to the COVID-19 pandemic the conference was held online. The 36 full papers and 7 short papers were thorougly reviewed and selected from a total of 113 qualified submissions. The papers present resent research on such topics as neural network theory, and cognitive sciences, machine learning, data mining, data security & privacy protection, and data-driven applications, computational intelligence, nature-inspired optimizers, and their engineering applications, cloud/edge/fog computing, the Internet of Things/Vehicles (IoT/IoV), and their system optimization, control systems, network synchronization, system integration, and industrial artificial intelligence, fuzzy logic, neuro-fuzzy systems, decision making, and their applications in management sciences, computer vision, image processing, and their industrial applications, and natural language processing, machine translation, knowledge graphs, and their applications.

Artificial Neural Network Modelling

Author : Subana Shanmuganathan
Publisher : Springer
ISBN 13 : 3319284959
Total Pages : 468 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Artificial Neural Network Modelling by : Subana Shanmuganathan

Download or read book Artificial Neural Network Modelling written by Subana Shanmuganathan and published by Springer. This book was released on 2016-02-03 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling.

Fundamentals of Artificial Neural Networks

Author : Mohamad H. Hassoun
Publisher : MIT Press
ISBN 13 : 9780262082396
Total Pages : 546 pages
Book Rating : 4.0/5 (823 download)

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Book Synopsis Fundamentals of Artificial Neural Networks by : Mohamad H. Hassoun

Download or read book Fundamentals of Artificial Neural Networks written by Mohamad H. Hassoun and published by MIT Press. This book was released on 1995 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: A systematic account of artificial neural network paradigms that identifies fundamental concepts and major methodologies. Important results are integrated into the text in order to explain a wide range of existing empirical observations and commonly used heuristics.

Engineering Applications of Bio-Inspired Artificial Neural Networks

Author : Jose Mira
Publisher : Springer Science & Business Media
ISBN 13 : 9783540660682
Total Pages : 942 pages
Book Rating : 4.6/5 (66 download)

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Book Synopsis Engineering Applications of Bio-Inspired Artificial Neural Networks by : Jose Mira

Download or read book Engineering Applications of Bio-Inspired Artificial Neural Networks written by Jose Mira and published by Springer Science & Business Media. This book was released on 1999-05-19 with total page 942 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes, together with its compagnion LNCS 1606, the refereed proceedings of the International Work-Conference on Artificial and Neural Networks, IWANN'99, held in Alicante, Spain in June 1999. The 91 revised papers presented were carefully reviewed and selected for inclusion in the book. This volume is devoted to applications of biologically inspired artificial neural networks in various engineering disciplines. The papers are organized in parts on artificial neural nets simulation and implementation, image processing, and engineering applications.

Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation

Author : Igor V. Tetko
Publisher : Springer Nature
ISBN 13 : 3030304876
Total Pages : 848 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation by : Igor V. Tetko

Download or read book Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation written by Igor V. Tetko and published by Springer Nature. This book was released on 2019-09-09 with total page 848 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.

Combining Artificial Neural Nets

Author : Amanda J.C. Sharkey
Publisher : Springer Science & Business Media
ISBN 13 : 1447107934
Total Pages : 300 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Combining Artificial Neural Nets by : Amanda J.C. Sharkey

Download or read book Combining Artificial Neural Nets written by Amanda J.C. Sharkey and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, written by leading researchers, presents methods of combining neural nets to improve their performance. The techniques include ensemble-based approaches, where a variety of methods are used to create a set of different nets trained on the same task, and modular approaches, where a task is decomposed into simpler problems. The techniques are also accompanied by an evaluation of their relative effectiveness and their application to a variety of problems.

Neural Networks and Analog Computation

Author : Hava T. Siegelmann
Publisher : Springer Science & Business Media
ISBN 13 : 146120707X
Total Pages : 193 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Neural Networks and Analog Computation by : Hava T. Siegelmann

Download or read book Neural Networks and Analog Computation written by Hava T. Siegelmann and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: The theoretical foundations of Neural Networks and Analog Computation conceptualize neural networks as a particular type of computer consisting of multiple assemblies of basic processors interconnected in an intricate structure. Examining these networks under various resource constraints reveals a continuum of computational devices, several of which coincide with well-known classical models. On a mathematical level, the treatment of neural computations enriches the theory of computation but also explicated the computational complexity associated with biological networks, adaptive engineering tools, and related models from the fields of control theory and nonlinear dynamics. The material in this book will be of interest to researchers in a variety of engineering and applied sciences disciplines. In addition, the work may provide the base of a graduate-level seminar in neural networks for computer science students.

Artificial Neural Networks in Biological and Environmental Analysis

Author : Grady Hanrahan
Publisher : CRC Press
ISBN 13 : 1439812594
Total Pages : 206 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Artificial Neural Networks in Biological and Environmental Analysis by : Grady Hanrahan

Download or read book Artificial Neural Networks in Biological and Environmental Analysis written by Grady Hanrahan and published by CRC Press. This book was released on 2011-01-18 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originating from models of biological neural systems, artificial neural networks (ANN) are the cornerstones of artificial intelligence research. Catalyzed by the upsurge in computational power and availability, and made widely accessible with the co-evolution of software, algorithms, and methodologies, artificial neural networks have had a profound

Soft Computing for Reservoir Characterization and Modeling

Author : Patrick Wong
Publisher : Physica
ISBN 13 : 3790818070
Total Pages : 582 pages
Book Rating : 4.7/5 (98 download)

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Book Synopsis Soft Computing for Reservoir Characterization and Modeling by : Patrick Wong

Download or read book Soft Computing for Reservoir Characterization and Modeling written by Patrick Wong and published by Physica. This book was released on 2013-11-11 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the middle of the 20th century, Genrich Altshuller, a Russian engineer, analysed hundreds of thousands of patents and scientific publications. From this analysis, he developed TRIZ (G. Altshuller, "40 Principles: TRIZ Keys to Technical Innovation. TRIZ Tools," Volume 1, First Edition, Technical Innovation Center, Inc. , Worcester, MA, January 1998; Y. Salamatov, "TRIZ: The Right Solution at the Right Time. A Guide to Innovative Problem Solving. " Insytec B. V. , 1999), the theory of inventive problem solving, together with a series of practical tools for helping engineers solving technical problems. Among these tools and theories, the substance-field theory gives a structured way of representing problems, the patterns of evolution show the lifecycle of technical systems, the contradiction matrix tells you how to resolve technical contradictions, using the forty principles that describe common ways of improving technical systems. For example, if you want to increase the strength of a device, without adding too much extra weight to it, the contradiction matrix tells you that you can use "Principle 1: Segmentation," or "Principle 8: Counterweight," or "Principle 15: Dynamicity," or "Principle 40: Composite Materials. " I really like two particular ones: "Principle 1: Segmentation," and Principle 15: Dynamicity. " "Segmentation" shows how systems evolve from an initial monolithic form into a set of independent parts, then eventually increasing the number of parts until each part becomes small enough that it cannot be identified anymore.

Multivariate Statistical Machine Learning Methods for Genomic Prediction

Author : Osval Antonio Montesinos López
Publisher : Springer Nature
ISBN 13 : 3030890104
Total Pages : 707 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Multivariate Statistical Machine Learning Methods for Genomic Prediction by : Osval Antonio Montesinos López

Download or read book Multivariate Statistical Machine Learning Methods for Genomic Prediction written by Osval Antonio Montesinos López and published by Springer Nature. This book was released on 2022-02-14 with total page 707 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.

Information Computing And Automation (In 3 Volumes) - Proceedings Of The International Conference

Author : Jian Ping Li
Publisher : World Scientific
ISBN 13 : 9814471380
Total Pages : 1645 pages
Book Rating : 4.8/5 (144 download)

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Book Synopsis Information Computing And Automation (In 3 Volumes) - Proceedings Of The International Conference by : Jian Ping Li

Download or read book Information Computing And Automation (In 3 Volumes) - Proceedings Of The International Conference written by Jian Ping Li and published by World Scientific. This book was released on 2008-04-25 with total page 1645 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wavelet analysis and its applications have become one of the fastest growing research areas in the past several years. Wavelet theory has been employed in many fields and applications, such as signal and image processing, communication systems, biomedical imaging, radar, air acoustics, and endless other areas. Active media technology is concerned with the development of autonomous computational or physical entities capable of perceiving, reasoning, adapting, learning, cooperating, and delegating in a dynamic environment.This book consists of carefully selected and received papers presented at the conference, and is an attempt to capture the essence of the current state-of-the-art in wavelet analysis and active media technology. Invited papers included in this proceedings includes contributions from Prof P Zhang, T D Bui, and C Y Suen from Concordia University, Canada; Prof N A Strelkov and V L Dol'nikov from Yaroslavl State University, Russia; Prof Chin-Chen Chang and Ching-Yun Chang from Taiwan; Prof S S Pandey from R D University, India; and Prof I L Bloshanskii from Moscow State Regional University, Russia.