New Developments in Artificial Neural Networks Research
Author: Robert W. Nelson, 4th
Publisher: Nova Science Publishers
Published: 2011
Total Pages: 356
ISBN-13: 9781620819647
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Artificial Neural Networks
Author: Gayle Cain
Publisher: Nova Science Publishers
Published: 2016-12
Total Pages: 0
ISBN-13: 9781634859646
DOWNLOAD EBOOKThis current book provides new research on artificial neural networks (ANNs). Topics discussed include the application of ANNs in chemistry and chemical engineering fields; the application of ANNs in the prediction of biodiesel fuel properties from fatty acid constituents; the use of ANNs for solar radiation estimation; the use of in silico methods to design and evaluate skin UV filters; a practical model based on the multilayer perceptron neural network (MLP) approach to predict the milling tool flank wear in a regular cut, as well as entry cut and exit cut, of a milling tool; parameter extraction of small-signal and noise models of microwave transistors based on ANNs; and the application of ANNs to deep-learning and predictive analysis in semantic TCM telemedicine systems.
Recent Advances in Artificial Neural Networks
Author: L. C. Jain
Publisher: CRC Press
Published: 2018-05-04
Total Pages: 372
ISBN-13: 1351084666
DOWNLOAD EBOOKNeural networks represent a new generation of information processing paradigms designed to mimic-in a very limited sense-the human brain. They can learn, recall, and generalize from training data, and with their potential applications limited only by the imaginations of scientists and engineers, they are commanding tremendous popularity and research interest. Over the last four decades, researchers have reported a number of neural network paradigms, however, the newest of these have not appeared in book form-until now. Recent Advances in Artificial Neural Networks collects the latest neural network paradigms and reports on their promising new applications. World-renowned experts discuss the use of neural networks in pattern recognition, color induction, classification, cluster detection, and more. Application engineers, scientists, and research students from all disciplines with an interest in considering neural networks for solving real-world problems will find this collection useful.
Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications
Author: Zhang, Ming
Publisher: IGI Global
Published: 2010-02-28
Total Pages: 660
ISBN-13: 1615207120
DOWNLOAD EBOOK"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.
Artificial Intelligence in the Age of Neural Networks and Brain Computing
Author: Robert Kozma
Publisher: Academic Press
Published: 2023-10-27
Total Pages: 398
ISBN-13: 0323958168
DOWNLOAD EBOOKArtificial 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
Growing Adaptive Machines
Author: Taras Kowaliw
Publisher: Springer
Published: 2014-06-11
Total Pages: 261
ISBN-13: 9783642553387
DOWNLOAD EBOOKThe 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.
Artificial Intelligence and Neural Networks
Author: F. Acar Savaci
Publisher: Springer Science & Business Media
Published: 2006-07-18
Total Pages: 236
ISBN-13: 3540367136
DOWNLOAD EBOOKThis book constitutes the thoroughly refereed post-proceedings of the 14th Turkish Symposium on Artificial Intelligence and Neural Networks, TAINN 2005, held in Izmir, Turkey, June 2005. The book presents 26 revised full papers categorized in topical sections on robotics, image processing, classification, learning theory and support vector machines, fuzzy neural networks, robotics, fuzzy logic, machine learning, engineering applications, and neural networks architecture.
Principles Of Artificial Neural Networks: Basic Designs To Deep Learning (4th Edition)
Author: Daniel Graupe
Publisher: World Scientific
Published: 2019-03-15
Total Pages: 439
ISBN-13: 9811201242
DOWNLOAD EBOOKThe field of Artificial Neural Networks is the fastest growing field in Information Technology and specifically, in Artificial Intelligence and Machine Learning.This must-have compendium presents the theory and case studies of artificial neural networks. The volume, with 4 new chapters, updates the earlier edition by highlighting recent developments in Deep-Learning Neural Networks, which are the recent leading approaches to neural networks. Uniquely, the book also includes case studies of applications of neural networks — demonstrating how such case studies are designed, executed and how their results are obtained.The title is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining.
Artificial Neural Network Modelling
Author: Subana Shanmuganathan
Publisher: Springer
Published: 2016-02-03
Total Pages: 468
ISBN-13: 3319284959
DOWNLOAD EBOOKThis 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.
Recent Trends in Artificial Neural Networks
Author: Ali Sadollah
Publisher: BoD – Books on Demand
Published: 2020-03-04
Total Pages: 152
ISBN-13: 1789854199
DOWNLOAD EBOOKArtificial intelligence (AI) is everywhere and it's here to stay. Most aspects of our lives are now touched by artificial intelligence in one way or another, from deciding what books or flights to buy online to whether our job applications are successful, whether we receive a bank loan, and even what treatment we receive for cancer. Artificial Neural Networks (ANNs) as a part of AI maintains the capacity to solve problems such as regression and classification with high levels of accuracy. This book aims to discuss the usage of ANNs for optimal solving of time series applications and clustering. Bounding of optimization methods particularly metaheuristics considered as global optimizers with ANNs make a strong and reliable prediction tool for handling real-life application. This book also demonstrates how different fields of studies utilize ANNs proving its wide reach and relevance.
