Matlab Neural Network Toolbox Users Guide

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Computer Neural Networks on MATLAB

Author : Daniel Okoh
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781539360957
Total Pages : 54 pages
Book Rating : 4.3/5 (69 download)

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Book Synopsis Computer Neural Networks on MATLAB by : Daniel Okoh

Download or read book Computer Neural Networks on MATLAB written by Daniel Okoh and published by Createspace Independent Publishing Platform. This book was released on 2016-10-07 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer neural networks are a branch of artificial intelligence, inspired to behave in a manner similar to the human brain; they are trained and they learn from their training. Computer neural networks have a wide variety of applications, mostly hinged around modelling, forecasting, and general predictions. This book illustrates how to use computer neural networks on MATLAB in very simple and elegant manner. The language of the book is elementary as it is meant for beginners, readers are notassumed to have previous skills on the subject. Projects, in varying degrees, have been used to make sure that readers get a practical and hands-on experience on the subject. The book is meant for you if you want to get a quick start with the practical use of computer neural networks on MATLAB without the boredom associated with a lengthy theoretical write-up.

Neural Network Design

Author : Martin T. Hagan
Publisher :
ISBN 13 : 9789812403766
Total Pages : pages
Book Rating : 4.4/5 (37 download)

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Book Synopsis Neural Network Design by : Martin T. Hagan

Download or read book Neural Network Design written by Martin T. Hagan and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Introduction to Neural Networks Using Matlab 6.0

Author : S. N. Sivanandam
Publisher : Tata McGraw-Hill Education
ISBN 13 : 9780070591127
Total Pages : 0 pages
Book Rating : 4.5/5 (911 download)

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Book Synopsis Introduction to Neural Networks Using Matlab 6.0 by : S. N. Sivanandam

Download or read book Introduction to Neural Networks Using Matlab 6.0 written by S. N. Sivanandam and published by Tata McGraw-Hill Education. This book was released on 2006 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

NETLAB

Author : Ian Nabney
Publisher : Springer Science & Business Media
ISBN 13 : 9781852334406
Total Pages : 444 pages
Book Rating : 4.3/5 (344 download)

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Book Synopsis NETLAB by : Ian Nabney

Download or read book NETLAB written by Ian Nabney and published by Springer Science & Business Media. This book was released on 2002 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Getting the most out of neural networks and related data modelling techniques is the purpose of this book. The text, with the accompanying Netlab toolbox, provides all the necessary tools and knowledge. Throughout, the emphasis is on methods that are relevant to the practical application of neural networks to pattern analysis problems. All parts of the toolbox interact in a coherent way, and implementations and descriptions of standard statistical techniques are provided so that they can be used as benchmarks against which more sophisticated algorithms can be evaluated. Plenty of examples and demonstration programs illustrate the theory and help the reader understand the algorithms and how to apply them.

MATLAB Primer

Author : Timothy A. Davis
Publisher : CRC Press
ISBN 13 : 1439828636
Total Pages : 232 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis MATLAB Primer by : Timothy A. Davis

Download or read book MATLAB Primer written by Timothy A. Davis and published by CRC Press. This book was released on 2010-08-18 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Highlighting the new aspects of MATLAB 7.10 and expanding on many existing features, this eighth edition continues to offer a hands-on, step-by-step introduction to using the powerful tools of MATLAB. It includes a new chapter on object-oriented programming, a new discussion of the MATLAB File Exchange window, major changes to the MATLAB Editor, and an explanation of more powerful Help tools. It also presents a synopsis of the most frequently used functions, operators, and special characters-providing quick and easy access to frequently used information. M-files and MEX-files for large examples are available at www.crcpress.com

Artificial Neural Nets and Genetic Algorithms

Author : Vera Kurkova
Publisher : Springer Science & Business Media
ISBN 13 : 3709162300
Total Pages : 518 pages
Book Rating : 4.7/5 (91 download)

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Book Synopsis Artificial Neural Nets and Genetic Algorithms by : Vera Kurkova

Download or read book Artificial Neural Nets and Genetic Algorithms written by Vera Kurkova and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first ICANNGA conference, devoted to biologically inspired computational paradigms, Neural Net works and Genetic Algorithms, was held in Innsbruck, Austria, in 1993. The meeting attracted researchers from all over Europe and further afield, who decided that this particular blend of topics should form a theme for a series of biennial conferences. The second meeting, held in Ales, France, in 1995, carried on the tradition set in Innsbruck of a relaxed and stimulating environment for the. exchange of ideas. The series has continued in Norwich, UK, in 1997, and Portoroz, Slovenia, in 1999. The Institute of Computer Science, Czech Academy of Sciences, is pleased to host the fifth conference in Prague. We have chosen the Liechtenstein palace under the Prague Castle as the conference site to enhance the traditionally good atmosphere of the meeting. There is an inspirational genius loci of the historical center of the city, where four hundred years ago a fruitful combination of theoretical and empirical method, through the collaboration of Johannes Kepler and Tycho de Brahe, led to the discovery of the laws of planetary orbits.

MATLAB for Machine Learning

Author : Giuseppe Ciaburro
Publisher : Packt Publishing Ltd
ISBN 13 : 1788399390
Total Pages : 374 pages
Book Rating : 4.7/5 (883 download)

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Book Synopsis MATLAB for Machine Learning by : Giuseppe Ciaburro

Download or read book MATLAB for Machine Learning written by Giuseppe Ciaburro and published by Packt Publishing Ltd. This book was released on 2017-08-28 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extract patterns and knowledge from your data in easy way using MATLAB About This Book Get your first steps into machine learning with the help of this easy-to-follow guide Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn Learn the introductory concepts of machine learning. Discover different ways to transform data using SAS XPORT, import and export tools, Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You'll start by getting your system ready with t he MATLAB environment for machine learning and you'll see how to easily interact with the Matlab workspace. We'll then move on to data cleansing, mining and analyzing various data types in machine learning and you'll see how to display data values on a plot. Next, you'll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You'll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you'll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.

MATLAB for Neuroscientists

Author : Pascal Wallisch
Publisher : Academic Press
ISBN 13 : 0123838371
Total Pages : 571 pages
Book Rating : 4.1/5 (238 download)

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Book Synopsis MATLAB for Neuroscientists by : Pascal Wallisch

Download or read book MATLAB for Neuroscientists written by Pascal Wallisch and published by Academic Press. This book was released on 2014-01-09 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: MATLAB for Neuroscientists serves as the only complete study manual and teaching resource for MATLAB, the globally accepted standard for scientific computing, in the neurosciences and psychology. This unique introduction can be used to learn the entire empirical and experimental process (including stimulus generation, experimental control, data collection, data analysis, modeling, and more), and the 2nd Edition continues to ensure that a wide variety of computational problems can be addressed in a single programming environment. This updated edition features additional material on the creation of visual stimuli, advanced psychophysics, analysis of LFP data, choice probabilities, synchrony, and advanced spectral analysis. Users at a variety of levels—advanced undergraduates, beginning graduate students, and researchers looking to modernize their skills—will learn to design and implement their own analytical tools, and gain the fluency required to meet the computational needs of neuroscience practitioners. - The first complete volume on MATLAB focusing on neuroscience and psychology applications - Problem-based approach with many examples from neuroscience and cognitive psychology using real data - Illustrated in full color throughout - Careful tutorial approach, by authors who are award-winning educators with strong teaching experience

Practical MATLAB Deep Learning

Author : Michael Paluszek
Publisher : Apress
ISBN 13 : 1484251245
Total Pages : 260 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Practical MATLAB Deep Learning by : Michael Paluszek

Download or read book Practical MATLAB Deep Learning written by Michael Paluszek and published by Apress. This book was released on 2020-02-07 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness the power of MATLAB for deep-learning challenges. This book provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. You’ll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. Along the way, you'll learn to model complex systems, including the stock market, natural language, and angles-only orbit determination. You’ll cover dynamics and control, and integrate deep-learning algorithms and approaches using MATLAB. You'll also apply deep learning to aircraft navigation using images. Finally, you'll carry out classification of ballet pirouettes using an inertial measurement unit to experiment with MATLAB's hardware capabilities. What You Will LearnExplore deep learning using MATLAB and compare it to algorithmsWrite a deep learning function in MATLAB and train it with examplesUse MATLAB toolboxes related to deep learningImplement tokamak disruption predictionWho This Book Is For Engineers, data scientists, and students wanting a book rich in examples on deep learning using MATLAB.

Global Sensitivity Analysis

Author : Andrea Saltelli
Publisher : John Wiley & Sons
ISBN 13 : 9780470725177
Total Pages : 304 pages
Book Rating : 4.7/5 (251 download)

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Book Synopsis Global Sensitivity Analysis by : Andrea Saltelli

Download or read book Global Sensitivity Analysis written by Andrea Saltelli and published by John Wiley & Sons. This book was released on 2008-02-28 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex mathematical and computational models are used in all areas of society and technology and yet model based science is increasingly contested or refuted, especially when models are applied to controversial themes in domains such as health, the environment or the economy. More stringent standards of proofs are demanded from model-based numbers, especially when these numbers represent potential financial losses, threats to human health or the state of the environment. Quantitative sensitivity analysis is generally agreed to be one such standard. Mathematical models are good at mapping assumptions into inferences. A modeller makes assumptions about laws pertaining to the system, about its status and a plethora of other, often arcane, system variables and internal model settings. To what extent can we rely on the model-based inference when most of these assumptions are fraught with uncertainties? Global Sensitivity Analysis offers an accessible treatment of such problems via quantitative sensitivity analysis, beginning with the first principles and guiding the reader through the full range of recommended practices with a rich set of solved exercises. The text explains the motivation for sensitivity analysis, reviews the required statistical concepts, and provides a guide to potential applications. The book: Provides a self-contained treatment of the subject, allowing readers to learn and practice global sensitivity analysis without further materials. Presents ways to frame the analysis, interpret its results, and avoid potential pitfalls. Features numerous exercises and solved problems to help illustrate the applications. Is authored by leading sensitivity analysis practitioners, combining a range of disciplinary backgrounds. Postgraduate students and practitioners in a wide range of subjects, including statistics, mathematics, engineering, physics, chemistry, environmental sciences, biology, toxicology, actuarial sciences, and econometrics will find much of use here. This book will prove equally valuable to engineers working on risk analysis and to financial analysts concerned with pricing and hedging.

Engineering Applications of MATLAB® 5.3 and SIMULINK® 3

Author : Mohand Mokhtari
Publisher : Springer Science & Business Media
ISBN 13 : 1447107411
Total Pages : 553 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Engineering Applications of MATLAB® 5.3 and SIMULINK® 3 by : Mohand Mokhtari

Download or read book Engineering Applications of MATLAB® 5.3 and SIMULINK® 3 written by Mohand Mokhtari and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written in two parts, the first revises the ideas and theoretical bases necessary for a good understanding of the techniques used in the second, which deals with applications of MATLAB(R) and SIMULINK(R) in process control and digital signal processing. Each application is treated through various techniques including the classical methods of automation and of deterministic and random digital processing using fuzzy logic and neural networks. The preceding mathematical study of the physical processes goes from finding the equations to editing the analogical model. The following SIMULINK(R) toolbox functions and blocks have been used: Control System, Signal Processing, Neural Network and Fuzzy Logic.

Seventh Symposium on Systems Analysis in Forest Resources

Author :
Publisher :
ISBN 13 :
Total Pages : 522 pages
Book Rating : 4.:/5 (89 download)

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Book Synopsis Seventh Symposium on Systems Analysis in Forest Resources by :

Download or read book Seventh Symposium on Systems Analysis in Forest Resources written by and published by . This book was released on 2000 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt:

General Technical Report NC.

Author :
Publisher :
ISBN 13 :
Total Pages : 736 pages
Book Rating : 4.E/5 ( download)

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Book Synopsis General Technical Report NC. by :

Download or read book General Technical Report NC. written by and published by . This book was released on 1998 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Neural Networks and Soft Computing

Author : Leszek Rutkowski
Publisher : Springer Science & Business Media
ISBN 13 : 3790819026
Total Pages : 935 pages
Book Rating : 4.7/5 (98 download)

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Book Synopsis Neural Networks and Soft Computing by : Leszek Rutkowski

Download or read book Neural Networks and Soft Computing written by Leszek Rutkowski and published by Springer Science & Business Media. This book was released on 2013-03-20 with total page 935 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents new trends and developments in soft computing techniques. Topics include: neural networks, fuzzy systems, evolutionary computation, knowledge discovery, rough sets, and hybrid methods. It also covers various applications of soft computing techniques in economics, mechanics, medicine, automatics and image processing. The book contains contributions from internationally recognized scientists, such as Zadeh, Bubnicki, Pawlak, Amari, Batyrshin, Hirota, Koczy, Kosinski, Novák, S.-Y. Lee, Pedrycz, Raudys, Setiono, Sincak, Strumillo, Takagi, Usui, Wilamowski and Zurada. An excellent overview of soft computing methods and their applications.

Power Electronics and Motor Drives

Author : Bimal K. Bose
Publisher : Academic Press
ISBN 13 : 0128238674
Total Pages : 1110 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Power Electronics and Motor Drives by : Bimal K. Bose

Download or read book Power Electronics and Motor Drives written by Bimal K. Bose and published by Academic Press. This book was released on 2020-11-13 with total page 1110 pages. Available in PDF, EPUB and Kindle. Book excerpt: Power Electronics and Motor Drives: Advances and Trends, Second Edition is the perfect resource to keep the electrical engineer up-to-speed on the latest advancements in technologies, equipment and applications. Carefully structured to include both traditional topics for entry-level and more advanced applications for the experienced engineer, this reference sheds light on the rapidly growing field of power electronic operations. New content covers converters, machine models and new control methods such as fuzzy logic and neural network control. This reference will help engineers further understand recent technologies and gain practical understanding with its inclusion of many industrial applications. Further supported by a glossary per chapter, this book gives engineers and researchers a critical reference to learn from real-world examples and make future decisions on power electronic technology and applications. - Provides many practical examples of industrial applications - Updates on the newest electronic topics with content added on fuzzy logic and neural networks - Presents information from an expert with decades of research and industrial experience

Gentle Introduction To Support Vector Machines In Biomedicine, A - Volume 2: Case Studies And Benchmarks

Author : Alexander Statnikov
Publisher : World Scientific Publishing Company
ISBN 13 : 9814518506
Total Pages : 210 pages
Book Rating : 4.8/5 (145 download)

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Book Synopsis Gentle Introduction To Support Vector Machines In Biomedicine, A - Volume 2: Case Studies And Benchmarks by : Alexander Statnikov

Download or read book Gentle Introduction To Support Vector Machines In Biomedicine, A - Volume 2: Case Studies And Benchmarks written by Alexander Statnikov and published by World Scientific Publishing Company. This book was released on 2013-03-21 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Support Vector Machines (SVMs) are among the most important recent developments in pattern recognition and statistical machine learning. They have found a great range of applications in various fields including biology and medicine. However, biomedical researchers often experience difficulties grasping both the theory and applications of these important methods because of lack of technical background. The purpose of this book is to introduce SVMs and their extensions and allow biomedical researchers to understand and apply them in real-life research in a very easy manner. The book is to consist of two volumes: theory and methods (Volume 1) and case studies (Volume 2).

Robust Intelligence and Trust in Autonomous Systems

Author : Ranjeev Mittu
Publisher : Springer
ISBN 13 : 148997668X
Total Pages : 277 pages
Book Rating : 4.4/5 (899 download)

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Book Synopsis Robust Intelligence and Trust in Autonomous Systems by : Ranjeev Mittu

Download or read book Robust Intelligence and Trust in Autonomous Systems written by Ranjeev Mittu and published by Springer. This book was released on 2016-04-07 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume explores the intersection of robust intelligence (RI) and trust in autonomous systems across multiple contexts among autonomous hybrid systems, where hybrids are arbitrary combinations of humans, machines and robots. To better understand the relationships between artificial intelligence (AI) and RI in a way that promotes trust between autonomous systems and human users, this book explores the underlying theory, mathematics, computational models, and field applications. It uniquely unifies the fields of RI and trust and frames it in a broader context, namely the effective integration of human-autonomous systems. A description of the current state of the art in RI and trust introduces the research work in this area. With this foundation, the chapters further elaborate on key research areas and gaps that are at the heart of effective human-systems integration, including workload management, human computer interfaces, team integration and performance, advanced analytics, behavior modeling, training, and, lastly, test and evaluation. Written by international leading researchers from across the field of autonomous systems research, Robust Intelligence and Trust in Autonomous Systems dedicates itself to thoroughly examining the challenges and trends of systems that exhibit RI, the fundamental implications of RI in developing trusted relationships with present and future autonomous systems, and the effective human systems integration that must result for trust to be sustained. Contributing authors: David W. Aha, Jenny Burke, Joseph Coyne, M.L. Cummings, Munjal Desai, Michael Drinkwater, Jill L. Drury, Michael W. Floyd, Fei Gao, Vladimir Gontar, Ayanna M. Howard, Mo Jamshidi, W.F. Lawless, Kapil Madathil, Ranjeev Mittu, Arezou Moussavi, Gari Palmer, Paul Robinette, Behzad Sadrfaridpour, Hamed Saeidi, Kristin E. Schaefer, Anne Selwyn, Ciara Sibley, Donald A. Sofge, Erin Solovey, Aaron Steinfeld, Barney Tannahill, Gavin Taylor, Alan R. Wagner, Yue Wang, Holly A. Yanco, Dan Zwillinger.