Neural Networks And Applications Using Matlab

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MATLAB Deep Learning

Author : Phil Kim
Publisher : Apress
ISBN 13 : 1484228456
Total Pages : 162 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis MATLAB Deep Learning by : Phil Kim

Download or read book MATLAB Deep Learning written by Phil Kim and published by Apress. This book was released on 2017-06-15 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB Deep Learning employs MATLAB as the underlying programming language and tool for the examples and case studies in this book. With this book, you'll be able to tackle some of today's real world big data, smart bots, and other complex data problems. You’ll see how deep learning is a complex and more intelligent aspect of machine learning for modern smart data analysis and usage. What You'll Learn Use MATLAB for deep learning Discover neural networks and multi-layer neural networks Work with convolution and pooling layers Build a MNIST example with these layers Who This Book Is For Those who want to learn deep learning using MATLAB. Some MATLAB experience may be useful.

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:

Dynamical Systems with Applications using MATLAB®

Author : Stephen Lynch
Publisher : Springer
ISBN 13 : 3319068202
Total Pages : 519 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Dynamical Systems with Applications using MATLAB® by : Stephen Lynch

Download or read book Dynamical Systems with Applications using MATLAB® written by Stephen Lynch and published by Springer. This book was released on 2014-07-22 with total page 519 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook, now in its second edition, provides a broad introduction to both continuous and discrete dynamical systems, the theory of which is motivated by examples from a wide range of disciplines. It emphasizes applications and simulation utilizing MATLAB®, Simulink®, the Image Processing Toolbox® and the Symbolic Math toolbox®, including MuPAD. Features new to the second edition include · sections on series solutions of ordinary differential equations, perturbation methods, normal forms, Gröbner bases, and chaos synchronization; · chapters on image processing and binary oscillator computing; · hundreds of new illustrations, examples, and exercises with solutions; and · over eighty up-to-date MATLAB program files and Simulink model files available online. These files were voted MATLAB Central Pick of the Week in July 2013. The hands-on approach of Dynamical Systems with Applications using MATLAB, Second Edition, has minimal prerequisites, only requiring familiarity with ordinary differential equations. It will appeal to advanced undergraduate and graduate students, applied mathematicians, engineers, and researchers in a broad range of disciplines such as population dynamics, biology, chemistry, computing, economics, nonlinear optics, neural networks, and physics. Praise for the first edition Summing up, it can be said that this text allows the reader to have an easy and quick start to the huge field of dynamical systems theory. MATLAB/SIMULINK facilitate this approach under the aspect of learning by doing. —OR News/Operations Research Spectrum The MATLAB programs are kept as simple as possible and the author's experience has shown that this method of teaching using MATLAB works well with computer laboratory classes of small sizes.... I recommend ‘Dynamical Systems with Applications using MATLAB’ as a good handbook for a diverse readership: graduates and professionals in mathematics, physics, science and engineering. —Mathematica

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.

Computational Methods for Deep Learning

Author : Wei Qi Yan
Publisher : Springer Nature
ISBN 13 : 3030610810
Total Pages : 134 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Computational Methods for Deep Learning by : Wei Qi Yan

Download or read book Computational Methods for Deep Learning written by Wei Qi Yan and published by Springer Nature. This book was released on 2020-12-04 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowledge transfer from the viewpoint of machine intelligence. It adopts the methodology from graphical theory, mathematical models, and algorithmic implementation, as well as covers datasets preparation, programming, results analysis and evaluations. Beginning with a grounding about artificial neural networks with neurons and the activation functions, the work then explains the mechanism of deep learning using advanced mathematics. In particular, it emphasizes how to use TensorFlow and the latest MATLAB deep-learning toolboxes for implementing deep learning algorithms. As a prerequisite, readers should have a solid understanding especially of mathematical analysis, linear algebra, numerical analysis, optimizations, differential geometry, manifold, and information theory, as well as basic algebra, functional analysis, and graphical models. This computational knowledge will assist in comprehending the subject matter not only of this text/reference, but also in relevant deep learning journal articles and conference papers. This textbook/guide is aimed at Computer Science research students and engineers, as well as scientists interested in deep learning for theoretic research and analysis. More generally, this book is also helpful for those researchers who are interested in machine intelligence, pattern analysis, natural language processing, and machine vision. Dr. Wei Qi Yan is an Associate Professor in the Department of Computer Science at Auckland University of Technology, New Zealand. His other publications include the Springer title, Visual Cryptography for Image Processing and Security.

Computational Intelligence Paradigms

Author : S. Sumathi
Publisher : CRC Press
ISBN 13 : 1439809038
Total Pages : 853 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Computational Intelligence Paradigms by : S. Sumathi

Download or read book Computational Intelligence Paradigms written by S. Sumathi and published by CRC Press. This book was released on 2010-01-05 with total page 853 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering a wide range of programming examples implemented in MATLAB, Computational Intelligence Paradigms: Theory and Applications Using MATLAB presents theoretical concepts and a general framework for computational intelligence (CI) approaches, including artificial neural networks, fuzzy systems, evolutionary computation, genetic algorithms and pr

Computational Intelligence Paradigms

Author : S.. PANEERSELVAM SUMATHI (SUREKHA.)
Publisher : CRC Press
ISBN 13 : 9780367384555
Total Pages : 851 pages
Book Rating : 4.3/5 (845 download)

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Book Synopsis Computational Intelligence Paradigms by : S.. PANEERSELVAM SUMATHI (SUREKHA.)

Download or read book Computational Intelligence Paradigms written by S.. PANEERSELVAM SUMATHI (SUREKHA.) and published by CRC Press. This book was released on 2019-08-30 with total page 851 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering a wide range of programming examples implemented in MATLAB(R), Computational Intelligence Paradigms: Theory and Applications Using MATLAB(R) presents theoretical concepts and a general framework for computational intelligence (CI) approaches, including artificial neural networks, fuzzy systems, evolutionary computation, genetic algorithms and programming, and swarm intelligence. It covers numerous intelligent computing methodologies and algorithms used in CI research. The book first focuses on neural networks, including common artificial neural networks; neural networks based on data classification, data association, and data conceptualization; and real-world applications of neural networks. It then discusses fuzzy sets, fuzzy rules, applications of fuzzy systems, and different types of fused neuro-fuzzy systems, before providing MATLAB illustrations of ANFIS, classification and regression trees, fuzzy c-means clustering algorithms, fuzzy ART map, and Takagi-Sugeno inference systems. The authors also describe the history, advantages, and disadvantages of evolutionary computation and include solved MATLAB programs to illustrate the implementation of evolutionary computation in various problems. After exploring the operators and parameters of genetic algorithms, they cover the steps and MATLAB routines of genetic programming. The final chapter introduces swarm intelligence and its applications, particle swarm optimization, and ant colony optimization. Full of worked examples and end-of-chapter questions, this comprehensive book explains how to use MATLAB to implement CI techniques for the solution of biological problems. It will help readers with their work on evolution dynamics, self-organization, natural and artificial morphogenesis, emergent collective behaviors, swarm intelligence, evolutionary strategies, genetic programming, and the evolution of social behaviors.

Neural Networks. Applications and Examples Using MATLAB

Author : J. Smith
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781544102436
Total Pages : 0 pages
Book Rating : 4.1/5 (24 download)

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Book Synopsis Neural Networks. Applications and Examples Using MATLAB by : J. Smith

Download or read book Neural Networks. Applications and Examples Using MATLAB written by J. Smith and published by Createspace Independent Publishing Platform. This book was released on 2017-02-24 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: MATLAB has the tool Neural Network Toolbox that provides algorithms, functions, and apps to create, train, visualize, and simulate neural networks. You can perform classification, regression, clustering, dimensionality reduction, time-series forecasting, and dynamic system modeling and control. The toolbox includes convolutional neural network and autoencoder deep learning algorithms for image classification and feature learning tasks. To speed up training of large data sets, you can distribute computations and data across multicore processors, GPUs, and computer clusters using Parallel Computing Toolbox. The more important features are the following: *Deep learning, including convolutional neural networks and autoencoders *Parallel computing and GPU support for accelerating training (with Parallel Computing Toolbox) *Supervised learning algorithms, including multilayer, radial basis, learning vector quantization (LVQ), time-delay, nonlinear autoregressive (NARX), and recurrent neural network (RNN) *Unsupervised learning algorithms, including self-organizing maps and competitive layers *Apps for data-fitting, pattern recognition, and clustering *Preprocessing, postprocessing, and network visualization for improving training efficiency and assessing network performance *Simulink(r) blocks for building and evaluating neural networks and for control systems applications

Dynamical Systems with Applications using MATLAB®

Author : Stephen Lynch
Publisher : Springer Science & Business Media
ISBN 13 : 0817681566
Total Pages : 458 pages
Book Rating : 4.8/5 (176 download)

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Book Synopsis Dynamical Systems with Applications using MATLAB® by : Stephen Lynch

Download or read book Dynamical Systems with Applications using MATLAB® written by Stephen Lynch and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: This introduction to dynamical systems theory guides readers through theory via example and the graphical MATLAB interface; the SIMULINK® accessory is used to simulate real-world dynamical processes. Examples included are from mechanics, electrical circuits, economics, population dynamics, epidemiology, nonlinear optics, materials science and neural networks. The book contains over 330 illustrations, 300 examples, and exercises with solutions.

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.

Neural Networks in Finance

Author : Paul D. McNelis
Publisher : Academic Press
ISBN 13 : 0124859674
Total Pages : 262 pages
Book Rating : 4.1/5 (248 download)

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Book Synopsis Neural Networks in Finance by : Paul D. McNelis

Download or read book Neural Networks in Finance written by Paul D. McNelis and published by Academic Press. This book was released on 2005-01-05 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction. McNelis utilizes a variety of examples, from forecasting automobile production and corporate bond spread, to inflation and deflation processes in Hong Kong and Japan, to credit card default in Germany to bank failures in Texas, to cap-floor volatilities in New York and Hong Kong. * Offers a balanced, critical review of the neural network methods and genetic algorithms used in finance * Includes numerous examples and applications * Numerical illustrations use MATLAB code and the book is accompanied by a website

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.

Application of Signal Processing Tools and Artificial Neural Network in Diagnosis of Power System Faults

Author : Nabamita Banerjee Roy
Publisher : CRC Press
ISBN 13 : 1000414906
Total Pages : 144 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Application of Signal Processing Tools and Artificial Neural Network in Diagnosis of Power System Faults by : Nabamita Banerjee Roy

Download or read book Application of Signal Processing Tools and Artificial Neural Network in Diagnosis of Power System Faults written by Nabamita Banerjee Roy and published by CRC Press. This book was released on 2021-07-21 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explores methods of fault identification through programming and simulation in MATLAB Examines signal processing tools and their applications with examples Provides knowledge of artificial neural networks and their applications with illustrations Uses PNN and BPNN to identify the different types of faults and obtain their corresponding locations Discusses the programming of signal processing using Wavelet Transform and S-Transform

The Perceptron

Author : Frank Rosenblatt
Publisher :
ISBN 13 :
Total Pages : 290 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis The Perceptron by : Frank Rosenblatt

Download or read book The Perceptron written by Frank Rosenblatt and published by . This book was released on 1958 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt:

MATLAB and Its Applications in Engineering

Author : Raj Kumar Bansal
Publisher : Pearson Education India
ISBN 13 : 9788131716816
Total Pages : 556 pages
Book Rating : 4.7/5 (168 download)

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Book Synopsis MATLAB and Its Applications in Engineering by : Raj Kumar Bansal

Download or read book MATLAB and Its Applications in Engineering written by Raj Kumar Bansal and published by Pearson Education India. This book was released on 2009 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book serves to be both a textbook and a reference for the theory and laboratory courses offered to undergraduate and graduate engineering students, and for practicing engineers.

Manual for the implementation of neural networks in MATLAB

Author : Michael Kuhn
Publisher : GRIN Verlag
ISBN 13 : 3638445518
Total Pages : 45 pages
Book Rating : 4.6/5 (384 download)

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Book Synopsis Manual for the implementation of neural networks in MATLAB by : Michael Kuhn

Download or read book Manual for the implementation of neural networks in MATLAB written by Michael Kuhn and published by GRIN Verlag. This book was released on 2005-12-05 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bachelor Thesis from the year 2005 in the subject Business economics - Information Management, grade: 2,0, Neisse University Görlitz (Neisse University), language: English, abstract: This bachelor thesis presents a manual about the implementation of neural networks in the software environment MATLAB. The thesis can be divided into four parts. After an introduction into the thesis, the theoretical background of neural networks and MATLAB is explained in two chapters. The third part is the description how to implement networks in a general way and with examples, too. The manual is created for the “Master Course of Computer Studies” at the University of Applied Science Zittau/Görlitz. Due to the fact, that this manual is a bachelor thesis just a small theoretical and practical overview about neural networks can be given.

Applications of Neural Networks in Electromagnetics

Author : Christos Christodoulou
Publisher : Artech House Publishers
ISBN 13 :
Total Pages : 544 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Applications of Neural Networks in Electromagnetics by : Christos Christodoulou

Download or read book Applications of Neural Networks in Electromagnetics written by Christos Christodoulou and published by Artech House Publishers. This book was released on 2001 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: The high-speed capabilities and learning abilities of neural networks can be applied to quickly solving numerous complex optimization problems in electromagnetics, and this book shows you how. Even if you have no background in neural networks, this book helps you understand the basics of each main network architecture in use today, including its strengths and limitations. Moreover, it gives you the knowledge you need to identify situations when the use of neural networks is the best problem-solving option.