Scientific and Technical Aerospace Reports

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Publisher :
ISBN 13 :
Total Pages : 1556 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Scientific and Technical Aerospace Reports by :

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1992 with total page 1556 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Proceedings of the 1992 IEEE International Symposium on Intelligent Control

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Publisher : Institute of Electrical & Electronics Engineers(IEEE)
ISBN 13 :
Total Pages : 644 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Proceedings of the 1992 IEEE International Symposium on Intelligent Control by : IEEE Control Systems Society

Download or read book Proceedings of the 1992 IEEE International Symposium on Intelligent Control written by IEEE Control Systems Society and published by Institute of Electrical & Electronics Engineers(IEEE). This book was released on 1992 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Learning and Soft Computing

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Publisher : MIT Press
ISBN 13 : 9780262112550
Total Pages : 556 pages
Book Rating : 4.1/5 (125 download)

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Book Synopsis Learning and Soft Computing by : Vojislav Kecman

Download or read book Learning and Soft Computing written by Vojislav Kecman and published by MIT Press. This book was released on 2001 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a thorough introduction to the field of learning from experimental data and soft computing. Support vector machines (SVM) and neural networks (NN) are the mathematical structures, or models, that underlie learning, while fuzzy logic systems (FLS) enable us to embed structured human knowledge into workable algorithms. The book assumes that it is not only useful, but necessary, to treat SVM, NN, and FLS as parts of a connected whole. Throughout, the theory and algorithms are illustrated by practical examples, as well as by problem sets and simulated experiments. This approach enables the reader to develop SVM, NN, and FLS in addition to understanding them. The book also presents three case studies: on NN-based control, financial time series analysis, and computer graphics. A solutions manual and all of the MATLAB programs needed for the simulated experiments are available.

Nonlinear System Identification

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Publisher : John Wiley & Sons
ISBN 13 : 1118535553
Total Pages : 611 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis Nonlinear System Identification by : Stephen A. Billings

Download or read book Nonlinear System Identification written by Stephen A. Billings and published by John Wiley & Sons. This book was released on 2013-07-29 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains describes a comprehensive framework for the identification and analysis of nonlinear dynamic systems in the time, frequency, and spatio-temporal domains. This book is written with an emphasis on making the algorithms accessible so that they can be applied and used in practice. Includes coverage of: The NARMAX (nonlinear autoregressive moving average with exogenous inputs) model The orthogonal least squares algorithm that allows models to be built term by term where the error reduction ratio reveals the percentage contribution of each model term Statistical and qualitative model validation methods that can be applied to any model class Generalised frequency response functions which provide significant insight into nonlinear behaviours A completely new class of filters that can move, split, spread, and focus energy The response spectrum map and the study of sub harmonic and severely nonlinear systems Algorithms that can track rapid time variation in both linear and nonlinear systems The important class of spatio-temporal systems that evolve over both space and time Many case study examples from modelling space weather, through identification of a model of the visual processing system of fruit flies, to tracking causality in EEG data are all included to demonstrate how easily the methods can be applied in practice and to show the insight that the algorithms reveal even for complex systems NARMAX algorithms provide a fundamentally different approach to nonlinear system identification and signal processing for nonlinear systems. NARMAX methods provide models that are transparent, which can easily be analysed, and which can be used to solve real problems. This book is intended for graduates, postgraduates and researchers in the sciences and engineering, and also for users from other fields who have collected data and who wish to identify models to help to understand the dynamics of their systems.

Identification of Nonlinear Systems Using Neural Networks and Polynomial Models

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Publisher : Springer Science & Business Media
ISBN 13 : 9783540231851
Total Pages : 220 pages
Book Rating : 4.2/5 (318 download)

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Book Synopsis Identification of Nonlinear Systems Using Neural Networks and Polynomial Models by : Andrzej Janczak

Download or read book Identification of Nonlinear Systems Using Neural Networks and Polynomial Models written by Andrzej Janczak and published by Springer Science & Business Media. This book was released on 2004-11-18 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph systematically presents the existing identification methods of nonlinear systems using the block-oriented approach It surveys various known approaches to the identification of Wiener and Hammerstein systems which are applicable to both neural network and polynomial models. The book gives a comparative study of their gradient approximation accuracy, computational complexity, and convergence rates and furthermore presents some new and original methods concerning the model parameter adjusting with gradient-based techniques. "Identification of Nonlinear Systems Using Neural Networks and Polynomal Models" is useful for researchers, engineers and graduate students in nonlinear systems and neural network theory.

Principles of Adaptive Filters and Self-learning Systems

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Publisher : Springer Science & Business Media
ISBN 13 : 9781852339845
Total Pages : 412 pages
Book Rating : 4.3/5 (398 download)

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Book Synopsis Principles of Adaptive Filters and Self-learning Systems by : Anthony Zaknich

Download or read book Principles of Adaptive Filters and Self-learning Systems written by Anthony Zaknich and published by Springer Science & Business Media. This book was released on 2005-04-25 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Teaches students about classical and nonclassical adaptive systems within one pair of covers Helps tutors with time-saving course plans, ready-made practical assignments and examination guidance The recently developed "practical sub-space adaptive filter" allows the reader to combine any set of classical and/or non-classical adaptive systems to form a powerful technology for solving complex nonlinear problems

A Hybrid Approach for Power Plant Fault Diagnostics

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Publisher : Springer
ISBN 13 : 3319718711
Total Pages : 283 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis A Hybrid Approach for Power Plant Fault Diagnostics by : Tamiru Alemu Lemma

Download or read book A Hybrid Approach for Power Plant Fault Diagnostics written by Tamiru Alemu Lemma and published by Springer. This book was released on 2017-12-30 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a hybrid approach to fault detection and diagnostics. It presents a detailed analysis related to practical applications of the fault detection and diagnostics framework, and highlights recent findings on power plant nonlinear model identification and fault diagnostics. The effectiveness of the methods presented is tested using data acquired from actual cogeneration and cooling plants (CCPs). The models presented were developed by applying Neuro-Fuzzy (NF) methods. The book offers a valuable resource for researchers and practicing engineers alike.

Advances In Intelligent Control

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Publisher : CRC Press
ISBN 13 : 9780748400669
Total Pages : 384 pages
Book Rating : 4.4/5 (6 download)

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Book Synopsis Advances In Intelligent Control by : C J Harris

Download or read book Advances In Intelligent Control written by C J Harris and published by CRC Press. This book was released on 1994-03-11 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Advances in intelligent Control" is a collection of essays covering the latest research in the field. Based on a special issue of "The International Journal of Control", the book is arranged in two parts. Part one contains recent contributions of artificial neural networks to modelling and control. Part two concerns itself primarily with aspects of fuzzy logic in intelligent control, guidance and estimation, although some of the contributions either make direct equivalence relationships to neural networks or use hybrid methods where a neural network is used to develop the fuzzy rule base.

Government Reports Annual Index

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Publisher :
ISBN 13 :
Total Pages : 1232 pages
Book Rating : 4.:/5 (89 download)

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Book Synopsis Government Reports Annual Index by :

Download or read book Government Reports Annual Index written by and published by . This book was released on 1992 with total page 1232 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Spatio-Temporal Modeling of Nonlinear Distributed Parameter Systems

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Publisher : Springer Science & Business Media
ISBN 13 : 940070741X
Total Pages : 175 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis Spatio-Temporal Modeling of Nonlinear Distributed Parameter Systems by : Han-Xiong Li

Download or read book Spatio-Temporal Modeling of Nonlinear Distributed Parameter Systems written by Han-Xiong Li and published by Springer Science & Business Media. This book was released on 2011-02-24 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein systems and their identifi cation methods. Then, the traditional Volterra model is extended to DPS, which results in the spatio-temporal Volterra model and its identification algorithm. All these methods are based on linear time/space separation. Sometimes, the nonlinear time/space separation can play a better role in modeling of very complex processes. Thus, a nonlinear time/space separation based neural modeling is also presented for a class of DPS with more complicated dynamics. Finally, all these modeling approaches are successfully applied to industrial thermal processes, including a catalytic rod, a packed-bed reactor and a snap curing oven. The work is presented giving a unifi ed view from time/space separation. The book also illustrates applications to thermal processes in the electronics packaging and chemical industry. This volume assumes a basic knowledge about distributed parameter systems, system modeling and identifi cation. It is intended for researchers, graduate students and engineers interested in distributed parameter systems, nonlinear systems, and process modeling and control.

Learning Algorithms

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Publisher : CRC Press
ISBN 13 : 1351090879
Total Pages : 251 pages
Book Rating : 4.3/5 (51 download)

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Book Synopsis Learning Algorithms by : P. Mars

Download or read book Learning Algorithms written by P. Mars and published by CRC Press. This book was released on 2018-01-18 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past decade, interest in computational or non-symbolic artificial intelligence has grown. The algorithms involved have the ability to learn from past experience, and therefore have significant potential in the adaptive control of signals and systems. This book focuses on the theory and applications of learning algorithms-stochastic learning automata; artificial neural networks; and genetic algorithms, evolutionary strategies, and evolutionary programming. Hybrid combinations of various algorithms are also discussed.Chapter 1 provides a brief overview of the topics discussed and organization of the text. The first half of the book (Chapters 2 through 4) discusses the basic theory of the learning algorithms, with one chapter devoted to each type. In the second half (Chapters 5 through 7), the emphasis is on a wide range of applications drawn from adaptive signal processing, system identification, and adaptive control problems in telecommunication networks.Learning Algorithms: Theory and Applications in Signal Processing, Control and Communications is an excellent text for final year undergraduate and first year graduate students in engineering, computer science, and related areas. Professional engineers and everyone involved in the application of learning techniques in adaptive signal processing, control, and communications will find this text a valuable synthesis of theory and practical application of the most useful algorithms.

Artificial Neural Networks for Modelling and Control of Non-Linear Systems

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Publisher : Springer Science & Business Media
ISBN 13 : 1475724934
Total Pages : 242 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Artificial Neural Networks for Modelling and Control of Non-Linear Systems by : Johan A.K. Suykens

Download or read book Artificial Neural Networks for Modelling and Control of Non-Linear Systems written by Johan A.K. Suykens and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks possess several properties that make them particularly attractive for applications to modelling and control of complex non-linear systems. Among these properties are their universal approximation ability, their parallel network structure and the availability of on- and off-line learning methods for the interconnection weights. However, dynamic models that contain neural network architectures might be highly non-linear and difficult to analyse as a result. Artificial Neural Networks for Modelling and Control of Non-Linear Systems investigates the subject from a system theoretical point of view. However the mathematical theory that is required from the reader is limited to matrix calculus, basic analysis, differential equations and basic linear system theory. No preliminary knowledge of neural networks is explicitly required. The book presents both classical and novel network architectures and learning algorithms for modelling and control. Topics include non-linear system identification, neural optimal control, top-down model based neural control design and stability analysis of neural control systems. A major contribution of this book is to introduce NLq Theory as an extension towards modern control theory, in order to analyze and synthesize non-linear systems that contain linear together with static non-linear operators that satisfy a sector condition: neural state space control systems are an example. Moreover, it turns out that NLq Theory is unifying with respect to many problems arising in neural networks, systems and control. Examples show that complex non-linear systems can be modelled and controlled within NLq theory, including mastering chaos. The didactic flavor of this book makes it suitable for use as a text for a course on Neural Networks. In addition, researchers and designers will find many important new techniques, in particular NLq emTheory, that have applications in control theory, system theory, circuit theory and Time Series Analysis.

Handbook of Neural Network Signal Processing

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Publisher : CRC Press
ISBN 13 : 1351836307
Total Pages : 417 pages
Book Rating : 4.3/5 (518 download)

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Book Synopsis Handbook of Neural Network Signal Processing by : Yu Hen Hu

Download or read book Handbook of Neural Network Signal Processing written by Yu Hen Hu and published by CRC Press. This book was released on 2018-10-03 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of neural networks is permeating every area of signal processing. They can provide powerful means for solving many problems, especially in nonlinear, real-time, adaptive, and blind signal processing. The Handbook of Neural Network Signal Processing brings together applications that were previously scattered among various publications to provide an up-to-date, detailed treatment of the subject from an engineering point of view. The authors cover basic principles, modeling, algorithms, architectures, implementation procedures, and well-designed simulation examples of audio, video, speech, communication, geophysical, sonar, radar, medical, and many other signals. The subject of neural networks and their application to signal processing is constantly improving. You need a handy reference that will inform you of current applications in this new area. The Handbook of Neural Network Signal Processing provides this much needed service for all engineers and scientists in the field.

Intelligent Systems

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Publisher : CRC Press
ISBN 13 : 1420040812
Total Pages : 2208 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Intelligent Systems by : Cornelius T. Leondes

Download or read book Intelligent Systems written by Cornelius T. Leondes and published by CRC Press. This book was released on 2018-10-08 with total page 2208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent systems, or artificial intelligence technologies, are playing an increasing role in areas ranging from medicine to the major manufacturing industries to financial markets. The consequences of flawed artificial intelligence systems are equally wide ranging and can be seen, for example, in the programmed trading-driven stock market crash of October 19, 1987. Intelligent Systems: Technology and Applications, Six Volume Set connects theory with proven practical applications to provide broad, multidisciplinary coverage in a single resource. In these volumes, international experts present case-study examples of successful practical techniques and solutions for diverse applications ranging from robotic systems to speech and signal processing, database management, and manufacturing.

Kybernetika

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Publisher :
ISBN 13 :
Total Pages : 656 pages
Book Rating : 4.E/5 ( download)

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Book Synopsis Kybernetika by :

Download or read book Kybernetika written by and published by . This book was released on 1993 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Nonlinearity in Structural Dynamics

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Publisher : CRC Press
ISBN 13 : 0429524986
Total Pages : 571 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Nonlinearity in Structural Dynamics by : K Worden

Download or read book Nonlinearity in Structural Dynamics written by K Worden and published by CRC Press. This book was released on 2019-04-23 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many types of engineering structures exhibit nonlinear behavior under real operating conditions. Sometimes the unpredicted nonlinear behavior of a system results in catastrophic failure. In civil engineering, grandstands at sporting events and concerts may be prone to nonlinear oscillations due to looseness of joints, friction, and crowd movements.

Computationally Efficient Model Predictive Control Algorithms

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Publisher : Springer Science & Business Media
ISBN 13 : 3319042297
Total Pages : 336 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Computationally Efficient Model Predictive Control Algorithms by : Maciej Ławryńczuk

Download or read book Computationally Efficient Model Predictive Control Algorithms written by Maciej Ławryńczuk and published by Springer Science & Business Media. This book was released on 2014-01-24 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include: · A few types of suboptimal MPC algorithms in which a linear approximation of the model or of the predicted trajectory is successively calculated on-line and used for prediction. · Implementation details of the MPC algorithms for feed forward perceptron neural models, neural Hammerstein models, neural Wiener models and state-space neural models. · The MPC algorithms based on neural multi-models (inspired by the idea of predictive control). · The MPC algorithms with neural approximation with no on-line linearization. · The MPC algorithms with guaranteed stability and robustness. · Cooperation between the MPC algorithms and set-point optimization. Thanks to linearization (or neural approximation), the presented suboptimal algorithms do not require demanding on-line nonlinear optimization. The presented simulation results demonstrate high accuracy and computational efficiency of the algorithms. For a few representative nonlinear benchmark processes, such as chemical reactors and a distillation column, for which the classical MPC algorithms based on linear models do not work properly, the trajectories obtained in the suboptimal MPC algorithms are very similar to those given by the ``ideal'' MPC algorithm with on-line nonlinear optimization repeated at each sampling instant. At the same time, the suboptimal MPC algorithms are significantly less computationally demanding.