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Author : John A. Flores
Publisher : Nova Science Publishers
ISBN 13 : 9781619421004
Total Pages : 410 pages
Book Rating : 4.4/5 (21 download)
Download or read book Focus on Artificial Neural Networks written by John A. Flores and published by Nova Science Publishers. This book was released on 2011 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : John A. Flores
Publisher :
ISBN 13 : 9781613242858
Total Pages : 410 pages
Book Rating : 4.2/5 (428 download)
Download or read book Focus on Artificial Neural Networks written by John A. Flores and published by . This book was released on 2011-01-01 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the most current research from across the globe in the study of artificial neural networks. Topics discussed include artificial neural networks in environmental sciences and chemical engineering; application of artificial neural networks in the development of pharamceutical microemulsions; massive-training artificial neural networks for supervised enhancement/suppression of lesions/patterns in medical images; evidences of new biophysical properties of microtubules; neural network applications in modern induction machine control systems and wavelet neural networks.
Author : Kishan Mehrotra
Publisher : MIT Press
ISBN 13 : 9780262133289
Total Pages : 376 pages
Book Rating : 4.1/5 (332 download)
Download or read book Elements of Artificial Neural Networks written by Kishan Mehrotra and published by MIT Press. This book was released on 1997 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elements of Artificial Neural Networks provides a clearly organized general introduction, focusing on a broad range of algorithms, for students and others who want to use neural networks rather than simply study them. The authors, who have been developing and team teaching the material in a one-semester course over the past six years, describe most of the basic neural network models (with several detailed solved examples) and discuss the rationale and advantages of the models, as well as their limitations. The approach is practical and open-minded and requires very little mathematical or technical background. Written from a computer science and statistics point of view, the text stresses links to contiguous fields and can easily serve as a first course for students in economics and management. The opening chapter sets the stage, presenting the basic concepts in a clear and objective way and tackling important -- yet rarely addressed -- questions related to the use of neural networks in practical situations. Subsequent chapters on supervised learning (single layer and multilayer networks), unsupervised learning, and associative models are structured around classes of problems to which networks can be applied. Applications are discussed along with the algorithms. A separate chapter takes up optimization methods. The most frequently used algorithms, such as backpropagation, are introduced early on, right after perceptrons, so that these can form the basis for initiating course projects. Algorithms published as late as 1995 are also included. All of the algorithms are presented using block-structured pseudo-code, and exercises are provided throughout. Software implementing many commonly used neural network algorithms is available at the book's website. Transparency masters, including abbreviated text and figures for the entire book, are available for instructors using the text.
Author : Sivanandam S., Paulraj M
Publisher : Vikas Publishing House
ISBN 13 : 9788125914259
Total Pages : 240 pages
Book Rating : 4.9/5 (142 download)
Download or read book Introduction to Artificial Neural Networks written by Sivanandam S., Paulraj M and published by Vikas Publishing House. This book was released on 2009-11-01 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: This fundamental book on Artificial Neural Networks has its emphasis on clear concepts, ease of understanding and simple examples. Written for undergraduate students, the book presents a large variety of standard neural networks with architecture, algorithms and applications.
Author : Zhang, Ming
Publisher : IGI Global
ISBN 13 : 1615207120
Total Pages : 660 pages
Book Rating : 4.6/5 (152 download)
Download or read book Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications written by Zhang, Ming and published by IGI Global. This book was released on 2010-02-28 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book introduces and explains Higher Order Neural Networks (HONNs) to people working in the fields of computer science and computer engineering, and how to use HONNS in these areas"--Provided by publisher.
Author : Doug Alexander
Publisher :
ISBN 13 : 9781536172331
Total Pages : 232 pages
Book Rating : 4.1/5 (723 download)
Download or read book Neural Networks written by Doug Alexander and published by . This book was released on 2020 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: "With respect to the ever-increasing developments in artificial intelligence and artificial neural network applications in different scopes such as medicine, industry, biology, history, military industries, recognition science, space, machine learning and etc., Neural Networks: History and Applications first discusses a comprehensive investigation of artificial neural networks. Next, the authors focus on studies carried out with the artificial neural network approach on the emotion recognition from 2D facial expressions between 2009 and 2019. The major objective of this study is to review, identify, evaluate and analyze the performance of artificial neural network models in emotion recognition applications. This compilation also proposes a simple nonlinear approach for dipole mode index prediction where past values of dipole mode index were used as inputs, and future values were predicted by artificial neural networks. The study was also conducted for seasonal dipole mode index prediction because the dipole mode index is more prominent in the Sep-Oct-Nov season. A subsequent study focuses on how mammography has a high false negative and false positive rate. As such, computer-aided diagnosis systems have been commercialized to help in micro-calcification detection and malignancy differentiation. Yet, little has been explored in differentiating breast cancers with artificial neural networks, one example of computer-aided diagnosis systems. The authors aim to bridge this gap in research. The penultimate chapter reviews the general conditions under which synaptic plasticity most effectively takes place to support the supervised learning of a precise temporal code. Then, the accuracy of each plasticity rule with respect to its temporal encoding precision is examined, and the maximum number of input patterns it can memorize using the precise timings of individual spikes as an indicator of storage capacity in different control and recognition tasks is explored. In closing, a case study is presented centered on an intelligent decision support system that is built on a neural network model based on the Encog machine learning framework to predict cryptocurrency close prices"--
Author : Bernhard Mehlig
Publisher : Cambridge University Press
ISBN 13 : 1108849563
Total Pages : 262 pages
Book Rating : 4.1/5 (88 download)
Download or read book Machine Learning with Neural Networks written by Bernhard Mehlig and published by Cambridge University Press. This book was released on 2021-10-28 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This modern and self-contained book offers a clear and accessible introduction to the important topic of machine learning with neural networks. In addition to describing the mathematical principles of the topic, and its historical evolution, strong connections are drawn with underlying methods from statistical physics and current applications within science and engineering. Closely based around a well-established undergraduate course, this pedagogical text provides a solid understanding of the key aspects of modern machine learning with artificial neural networks, for students in physics, mathematics, and engineering. Numerous exercises expand and reinforce key concepts within the book and allow students to hone their programming skills. Frequent references to current research develop a detailed perspective on the state-of-the-art in machine learning research.
Author : Taras Kowaliw
Publisher : Springer
ISBN 13 : 3642553370
Total Pages : 266 pages
Book Rating : 4.6/5 (425 download)
Download or read book Growing Adaptive Machines written by Taras Kowaliw and published by Springer. This book was released on 2014-06-04 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The pursuit of artificial intelligence has been a highly active domain of research for decades, yielding exciting scientific insights and productive new technologies. In terms of generating intelligence, however, this pursuit has yielded only limited success. This book explores the hypothesis that adaptive growth is a means of moving forward. By emulating the biological process of development, we can incorporate desirable characteristics of natural neural systems into engineered designs and thus move closer towards the creation of brain-like systems. The particular focus is on how to design artificial neural networks for engineering tasks. The book consists of contributions from 18 researchers, ranging from detailed reviews of recent domains by senior scientists, to exciting new contributions representing the state of the art in machine learning research. The book begins with broad overviews of artificial neurogenesis and bio-inspired machine learning, suitable both as an introduction to the domains and as a reference for experts. Several contributions provide perspectives and future hypotheses on recent highly successful trains of research, including deep learning, the Hyper NEAT model of developmental neural network design, and a simulation of the visual cortex. Other contributions cover recent advances in the design of bio-inspired artificial neural networks, including the creation of machines for classification, the behavioural control of virtual agents, the desi gn of virtual multi-component robots and morphologies and the creation of flexible intelligence. Throughout, the contributors share their vast expertise on the means and benefits of creating brain-like machines. This book is appropriate for advanced students and practitioners of artificial intelligence and machine learning.
Author : Richard Segall
Publisher : Engineering Science Reference
ISBN 13 : 9781799884552
Total Pages : pages
Book Rating : 4.8/5 (845 download)
Download or read book Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning written by Richard Segall and published by Engineering Science Reference. This book was released on 2021-11 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book covers applications of artificial neural networks (ANN) and machine learning (ML) aspects of artificial intelligence to applications to the biomedical and business world including their interface to applications for screening for diseases to applications to large-scale credit card purchasing patterns"--
Author : Chi Leung Patrick Hui
Publisher : BoD – Books on Demand
ISBN 13 : 9533071885
Total Pages : 602 pages
Book Rating : 4.5/5 (33 download)
Download or read book Artificial Neural Networks written by Chi Leung Patrick Hui and published by BoD – Books on Demand. This book was released on 2011-04-11 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers 27 articles in the applications of artificial neural networks (ANN) in various disciplines which includes business, chemical technology, computing, engineering, environmental science, science and nanotechnology. They modeled the ANN with verification in different areas. They demonstrated that the ANN is very useful model and the ANN could be applied in problem solving and machine learning. This book is suitable for all professionals and scientists in understanding how ANN is applied in various areas.
Author : V. Rao Vemuri
Publisher :
ISBN 13 :
Total Pages : 168 pages
Book Rating : 4.3/5 (91 download)
Download or read book Artificial Neural Networks written by V. Rao Vemuri and published by . This book was released on 1988 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides an introduction to the field of artificial neural networks, and their role in the emerging field of neurocomputing, and the theoretical concepts that are the focus of current research. The genesis of this subject can be traced back to the 1940s, while present interest is due to recent developments in theoretical models, technologies, and algorithms. The papers selected for this volume were published primarily in IEEE journals.
Author : Vladimir Golovko
Publisher : Springer
ISBN 13 : 3319082019
Total Pages : 222 pages
Book Rating : 4.3/5 (19 download)
Download or read book Neural Networks and Artificial Intelligence written by Vladimir Golovko and published by Springer. This book was released on 2014-05-27 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Conference on Neural Networks and Artificial Intelligence, ICNNAI 2014, held in Brest, Belarus, in June 2014. The 19 revised full papers presented were carefully reviewed and selected from 27 submissions. The papers are organized in topical sections on forest resource management; artificial intelligence by neural networks; optimization; classification; fuzzy approach; machine intelligence; analytical approach; mobile robot; real world application.
Author : Kasra Esfandiari
Publisher : Springer Nature
ISBN 13 : 3030731367
Total Pages : 181 pages
Book Rating : 4.0/5 (37 download)
Download or read book Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems written by Kasra Esfandiari and published by Springer Nature. This book was released on 2021-06-18 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: The focus of this book is the application of artificial neural networks in uncertain dynamical systems. It explains how to use neural networks in concert with adaptive techniques for system identification, state estimation, and control problems. The authors begin with a brief historical overview of adaptive control, followed by a review of mathematical preliminaries. In the subsequent chapters, they present several neural network-based control schemes. Each chapter starts with a concise introduction to the problem under study, and a neural network-based control strategy is designed for the simplest case scenario. After these designs are discussed, different practical limitations (i.e., saturation constraints and unavailability of all system states) are gradually added, and other control schemes are developed based on the primary scenario. Through these exercises, the authors present structures that not only provide mathematical tools for navigating control problems, but also supply solutions that are pertinent to real-life systems.
Author : Segall, Richard S.
Publisher : IGI Global
ISBN 13 : 1799884570
Total Pages : 394 pages
Book Rating : 4.7/5 (998 download)
Download or read book Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning written by Segall, Richard S. and published by IGI Global. This book was released on 2022-01-07 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: During these uncertain and turbulent times, intelligent technologies including artificial neural networks (ANN) and machine learning (ML) have played an incredible role in being able to predict, analyze, and navigate unprecedented circumstances across a number of industries, ranging from healthcare to hospitality. Multi-factor prediction in particular has been especially helpful in dealing with the most current pressing issues such as COVID-19 prediction, pneumonia detection, cardiovascular diagnosis and disease management, automobile accident prediction, and vacation rental listing analysis. To date, there has not been much research content readily available in these areas, especially content written extensively from a user perspective. Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning is designed to cover a brief and focused range of essential topics in the field with perspectives, models, and first-hand experiences shared by prominent researchers, discussing applications of artificial neural networks (ANN) and machine learning (ML) for biomedical and business applications and a listing of current open-source software for neural networks, machine learning, and artificial intelligence. It also presents summaries of currently available open source software that utilize neural networks and machine learning. The book is ideal for professionals, researchers, students, and practitioners who want to more fully understand in a brief and concise format the realm and technologies of artificial neural networks (ANN) and machine learning (ML) and how they have been used for prediction of multi-disciplinary research problems in a multitude of disciplines.
Author : Robert Kozma
Publisher : Academic Press
ISBN 13 : 0323958168
Total Pages : 398 pages
Book Rating : 4.3/5 (239 download)
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 2023-10-27 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
Author : Yusuke Sugomori
Publisher : Packt Publishing Ltd
ISBN 13 : 1788471717
Total Pages : 744 pages
Book Rating : 4.7/5 (884 download)
Download or read book Deep Learning: Practical Neural Networks with Java written by Yusuke Sugomori and published by Packt Publishing Ltd. This book was released on 2017-06-08 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build and run intelligent applications by leveraging key Java machine learning libraries About This Book Develop a sound strategy to solve predictive modelling problems using the most popular machine learning Java libraries. Explore a broad variety of data processing, machine learning, and natural language processing through diagrams, source code, and real-world applications This step-by-step guide will help you solve real-world problems and links neural network theory to their application Who This Book Is For This course is intended for data scientists and Java developers who want to dive into the exciting world of deep learning. It will get you up and running quickly and provide you with the skills you need to successfully create, customize, and deploy machine learning applications in real life. What You Will Learn Get a practical deep dive into machine learning and deep learning algorithms Explore neural networks using some of the most popular Deep Learning frameworks Dive into Deep Belief Nets and Stacked Denoising Autoencoders algorithms Apply machine learning to fraud, anomaly, and outlier detection Experiment with deep learning concepts, algorithms, and the toolbox for deep learning Select and split data sets into training, test, and validation, and explore validation strategies Apply the code generated in practical examples, including weather forecasting and pattern recognition In Detail Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognitionStarting with an introduction to basic machine learning algorithms, this course takes you further into this vital world of stunning predictive insights and remarkable machine intelligence. This course helps you solve challenging problems in image processing, speech recognition, language modeling. You will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text. You will also work with examples such as weather forecasting, disease diagnosis, customer profiling, generalization, extreme machine learning and more. By the end of this course, you will have all the knowledge you need to perform deep learning on your system with varying complexity levels, to apply them to your daily work. The course provides you with highly practical content explaining deep learning with Java, from the following Packt books: Java Deep Learning Essentials Machine Learning in Java Neural Network Programming with Java, Second Edition Style and approach This course aims to create a smooth learning path that will teach you how to effectively use deep learning with Java with other de facto components to get the most out of it. Through this comprehensive course, you'll learn the basics of predictive modelling and progress to solve real-world problems and links neural network theory to their application
Author : S?ren Brunak
Publisher : World Scientific
ISBN 13 : 9789971509385
Total Pages : 200 pages
Book Rating : 4.5/5 (93 download)
Download or read book Neural Networks written by S?ren Brunak and published by World Scientific. This book was released on 1990 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Both specialists and laymen will enjoy reading this book. Using a lively, non-technical style and images from everyday life, the authors present the basic principles behind computing and computers. The focus is on those aspects of computation that concern networks of numerous small computational units, whether biological neural networks or artificial electronic devices.
