Neural Logic Networks

Author : Hoon-Heng Teh
Publisher : World Scientific
Page : 520 pages
File Size : 55,7 Mb
Release : 1995-10-25
Category : Computers
ISBN : 9789814501781

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Neural Logic Networks by Hoon-Heng Teh Pdf

This book is the first of a series of technical reports of a key research project of the Real-World Computing Program supported by the MITI of Japan. The main goal of the project is to model human intelligence by a special class of mathematical systems called neural logic networks. The book consists of three parts. Part 1 describes the general theory of neural logic networks and their potential applications. Part 2 discusses a new logic called Neural Logic which attempts to emulate more closely the logical thinking process of human. Part 3 studies the special features of neural logic networks which resemble the human intuition process. This book should appeal to researchers in artificial intelligence, neural computings and logic, as well as graduate and advance undergraduate students in computer science. Contents:What are Neural Logic Networks? — A Gentle Introduction to the Study of a New Class of Neural Networks Called Neural Logic NetworksNeural Logic Networks and Human Logical ReasoningNeural Logic and Human IntuitionReferencesIndex Readership: Researchers in artificial intelligence, neural computings and logic, graduate and advance undergraduate students in computer science. keywords:Neural Networks;MITI;Logical Reasoning;Neural Logic;Human Intuition;Artificial Intelligence;Neural Computings

Author : József Dombi,Orsolya Csiszár
Publisher : Springer Nature
Page : 186 pages
File Size : 47,9 Mb
Release : 2021-04-28
Category : Technology & Engineering
ISBN : 9783030722807

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Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools by József Dombi,Orsolya Csiszár Pdf

The research presented in this book shows how combining deep neural networks with a special class of fuzzy logical rules and multi-criteria decision tools can make deep neural networks more interpretable – and even, in many cases, more efficient. Fuzzy logic together with multi-criteria decision-making tools provides very powerful tools for modeling human thinking. Based on their common theoretical basis, we propose a consistent framework for modeling human thinking by using the tools of all three fields: fuzzy logic, multi-criteria decision-making, and deep learning to help reduce the black-box nature of neural models; a challenge that is of vital importance to the whole research community.

Author : H. H. Teh
Publisher : World Scientific
Page : 526 pages
File Size : 45,5 Mb
Release : 1995
Category : Computers
ISBN : 9810224192

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Neural Logic Networks by H. H. Teh Pdf

This book is the first of a series of technical reports of a key research project of the Real-World Computing Program supported by the MITI of Japan.The main goal of the project is to model human intelligence by a special class of mathematical systems called neural logic networks.The book consists of three parts. Part 1 describes the general theory of neural logic networks and their potential applications. Part 2 discusses a new logic called Neural Logic which attempts to emulate more closely the logical thinking process of human. Part 3 studies the special features of neural logic networks which resemble the human intuition process.This book should appeal to researchers in artificial intelligence, neural computings and logic, as well as graduate and advance undergraduate students in computer science.

Author : Hayagriva V. Rao,BPB Publications
Publisher : Unknown
Page : 551 pages
File Size : 44,7 Mb
Release : 1996
Category : C++ (Computer program language)
ISBN : 8170296943

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C++ Neural Networks and Fuzzy Logic by Hayagriva V. Rao,BPB Publications Pdf

Author : Nikola K. Kasabov
Publisher : Marcel Alencar
Page : 581 pages
File Size : 55,8 Mb
Release : 1996
Category : Artificial intelligence
ISBN : 9780262112123

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Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering by Nikola K. Kasabov Pdf

Combines the study of neural networks and fuzzy systems with symbolic artificial intelligence (AI) methods to build comprehensive AI systems. Describes major AI problems (pattern recognition, speech recognition, prediction, decision-making, game-playing) and provides illustrative examples. Includes applications in engineering, business and finance.

Author : Stamatios V. Kartalopoulos
Publisher : Wiley-IEEE Press
Page : 240 pages
File Size : 55,5 Mb
Release : 1996
Category : Computers
ISBN : UOM:39015037336958

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Understanding Neural Networks and Fuzzy Logic by Stamatios V. Kartalopoulos Pdf

Understand the fundamentals of the emerging field of fuzzy neural networks, their applications and the most used paradigms with this carefully organized state-of-the-art textbook. Previously tested at a number of noteworthy conference tutorials, the simple numerical examples presented in this book provide excellent tools for progressive learning. UNDERSTANDING NEURAL NETWORKS AND FUZZY LOGIC offers a simple presentation and bottom-up approach that is ideal for working professional engineers, undergraduates, medical/biology majors, and anyone with a nonspecialist background. Sponsored by: IEEE Neural Networks Council

Author : Granino Arthur Korn
Publisher : MIT Press (MA)
Page : 418 pages
File Size : 47,8 Mb
Release : 1995
Category : Computers
ISBN : UOM:39015037338442

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Neural Networks and Fuzzy-logic Control on Personal Computers and Workstations by Granino Arthur Korn Pdf

Neural Networks and Fuzzy-Logic Control introduces a simple integrated environment for programming displays and report generation. It includes the only currently available software that permits combined simulation of multiple neural networks, fuzzy-logic controllers, and dynamic systems such as robots or physiological models. The enclosed educational version of DESIRE/NEUNET differs for the full system mainly in the size of its data area and includes a compiler, two screen editors, color graphics, and many ready-to-run examples. The software lets users or instructors add their own help screens and interactive menus. The version of DESIRE/NEUNET included here is for PCs, viz. 286/287, 386/387, 486DX, Pentium, P6, SX with math coprocessor.

Author : Duc T. Pham,Xing Liu
Publisher : Springer Science & Business Media
Page : 243 pages
File Size : 52,9 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9781447132448

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Neural Networks for Identification, Prediction and Control by Duc T. Pham,Xing Liu Pdf

In recent years, there has been a growing interest in applying neural networks to dynamic systems identification (modelling), prediction and control. Neural networks are computing systems characterised by the ability to learn from examples rather than having to be programmed in a conventional sense. Their use enables the behaviour of complex systems to be modelled and predicted and accurate control to be achieved through training, without a priori information about the systems' structures or parameters. This book describes examples of applications of neural networks In modelling, prediction and control. The topics covered include identification of general linear and non-linear processes, forecasting of river levels, stock market prices and currency exchange rates, and control of a time-delayed plant and a two-joint robot. These applications employ the major types of neural networks and learning algorithms. The neural network types considered in detail are the muhilayer perceptron (MLP), the Elman and Jordan networks and the Group-Method-of-Data-Handling (GMDH) network. In addition, cerebellar-model-articulation-controller (CMAC) networks and neuromorphic fuzzy logic systems are also presented. The main learning algorithm adopted in the applications is the standard backpropagation (BP) algorithm. Widrow-Hoff learning, dynamic BP and evolutionary learning are also described.

Author : Stephen I. Gallant
Publisher : MIT Press
Page : 392 pages
File Size : 55,5 Mb
Release : 1993
Category : Computers
ISBN : 0262071452

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Neural Network Learning and Expert Systems by Stephen I. Gallant Pdf

presents a unified and in-depth development of neural network learning algorithms and neural network expert systems

Author : Raul Rojas
Publisher : Springer Science & Business Media
Page : 511 pages
File Size : 48,8 Mb
Release : 2013-06-29
Category : Computers
ISBN : 9783642610684

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Neural Networks by Raul Rojas Pdf

Neural networks are a computing paradigm that is finding increasing attention among computer scientists. In this book, theoretical laws and models previously scattered in the literature are brought together into a general theory of artificial neural nets. Always with a view to biology and starting with the simplest nets, it is shown how the properties of models change when more general computing elements and net topologies are introduced. Each chapter contains examples, numerous illustrations, and a bibliography. The book is aimed at readers who seek an overview of the field or who wish to deepen their knowledge. It is suitable as a basis for university courses in neurocomputing.

Author : Chi-hau Chen
Publisher : McGraw-Hill Companies
Page : 862 pages
File Size : 51,6 Mb
Release : 1996
Category : Computers
ISBN : UOM:39015037342592

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Fuzzy Logic and Neural Network Handbook by Chi-hau Chen Pdf

A practical reference that presents concise and comprehensive reports on the major activities in fuzzy logic and neural networks, with emphasis on the applications and systems of interest to computer engineers. Each of the 31 chapters focuses on the most important activity of a specific topic, and the chapters are organized into three parts: principles and algorithms; applications; and architectures and systems. The applications for fuzzy logic include home appliance design and manufacturing process; those for neural networks include radar, sonar, and speech signal processing, remote sensing, and electrical power systems. Annotation copyright by Book News, Inc., Portland, OR

Author : Graupe Daniel
Publisher : World Scientific
Page : 440 pages
File Size : 43,6 Mb
Release : 2019-03-15
Category : Computers
ISBN : 9789811201240

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Principles Of Artificial Neural Networks: Basic Designs To Deep Learning (4th Edition) by Graupe Daniel Pdf

The 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.

Author : Berndt Müller,Joachim Reinhardt,Michael T. Strickland
Publisher : Springer Science & Business Media
Page : 358 pages
File Size : 44,6 Mb
Release : 1995-10-02
Category : Computers
ISBN : 3540602070

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Neural Networks by Berndt Müller,Joachim Reinhardt,Michael T. Strickland Pdf

Neural Networks presents concepts of neural-network models and techniques of parallel distributed processing in a three-step approach: - A brief overview of the neural structure of the brain and the history of neural-network modeling introduces to associative memory, preceptrons, feature-sensitive networks, learning strategies, and practical applications. - The second part covers subjects like statistical physics of spin glasses, the mean-field theory of the Hopfield model, and the "space of interactions" approach to the storage capacity of neural networks. - The final part discusses nine programs with practical demonstrations of neural-network models. The software and source code in C are on a 3 1/2" MS-DOS diskette can be run with Microsoft, Borland, Turbo-C, or compatible compilers.

Author : Mo-yuen Chow
Publisher : World Scientific
Page : 160 pages
File Size : 54,5 Mb
Release : 1997-11-26
Category : Computers
ISBN : 9789814496933

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Methodologies Of Using Neural Network And Fuzzy Logic Technologies For Motor Incipient Fault Detection by Mo-yuen Chow Pdf

Motor monitoring, incipient fault detection, and diagnosis are important and difficult topics in the engineering field. These topics deal with motors ranging from small DC motors used in intensive care units to the huge motors used in nuclear power plants. With proper machine monitoring and fault detection schemes, improved safety and reliability can be achieved for different engineering system operations. The importance of incipient fault detection can be found in the cost saving which can be obtained by detecting potential machine failures before they occur. Non-invasive, inexpensive, and reliable fault detection techniques are often preferred by many engineers. A large number of techniques, such as expert system approaches and vibration analysis, have been developed for motor fault detection purposes. Those techniques have achieved a certain degree of success. However, due to the complexity and importance of the systems, there is a need to further improve existing fault detection techniques.A major key to the success in fault detection is the ability to use appropriate technology to effectively fuse the relevant information to provide accurate and reliable results. The advance in technology will provide opportunities for improving existing fault detection schemes. With the maturing technology of artificial neural network and fuzzy logic, the motor fault detection problem can be solved using an innovative approach based on measurements that are easily accessible, without the need for rigorous mathematical models. This approach can identify and aggregate the relevant information for accurate and reliable motor fault detection. This book will introduce the neccessary concepts of neural network and fuzzy logic, describe the advantages and challenges of using these technologies to solve motor fault detection problems, and discuss several design considerations and methodologies in applying these techniques to motor incipient fault detection.

Author : Christopher M. Bishop
Publisher : Oxford University Press
Page : 501 pages
File Size : 44,9 Mb
Release : 1995-11-23
Category : Computers
ISBN : 9780198538646

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Neural Networks for Pattern Recognition by Christopher M. Bishop Pdf

Statistical pattern recognition; Probability density estimation; Single-layer networks; The multi-layer perceptron; Radial basis functions; Error functions; Parameter optimization algorithms; Pre-processing and feature extraction; Learning and generalization; Bayesian techniques; Appendix; References; Index.