Articles by "Computer Engineering"

Showing posts with label Computer Engineering. Show all posts

Michael Paluszek, Stephanie Thomas ... 326 pages - Publisher: Apress; (December, 2016) ... Language: English - ISBN-10: 1484222490 - ISBN-13: 978-1484222492.

This book is a comprehensive guide to machine learning with worked examples in MATLAB. It starts with an overview of the history of Artificial Intelligence and automatic control and how the field of machine learning grew from these. It provides descriptions of all major areas in machine learning. The book reviews commercially available packages for machine learning and shows how they fit into the field. The book then shows how MATLAB can be used to solve machine learning problems and how MATLAB graphics can enhance the programmer’s understanding of the results and help users of their software grasp the results. Machine Learning can be very mathematical. The mathematics for each area is introduced in a clear and concise form so that even casual readers can understand the math. Readers from all areas of engineering will see connections to what they know and will learn new technology. The book then provides complete solutions in MATLAB for several important problems in machine learning including face identification, autonomous driving, and data classification. Full source code is provided for all of the examples and applications in the book. What you'll learn: An overview of the field of machine learning - Commercial and open source packages in MATLAB - How to use MATLAB for programming and building machine learning applications - MATLAB graphics for machine learning. Practical real world examples in MATLAB for major applications of machine learning in big data. Who is this book for: The primary audiences are engineers and engineering students wanting a comprehensive and practical introduction to machine learning.

Kevin L. Priddy, Paul E. Keller ... 180 pages - Publisher: SPIE Publications; (August, 2005) ... Language: English - ISBN-10: 0819459879 - ISBN-13: 978-0819459879 ...

This tutorial text provides the reader with an understanding of artificial neural networks (ANNs) and their application, beginning with the biological systems which inspired them, through the learning methods that have been developed and the data collection processes, to the many ways ANNs are being used today.
The material is presented with a minimum of math (although the mathematical details are included in the appendices for interested readers), and with a maximum of hands-on experience. All specialized terms are included in a glossary. The result is a highly readable text that will teach the engineer the guiding principles necessary to use and apply artificial neural networks. Contents: - Preface - Acknowledgments - Introduction - Learning Methods - Data Normalization - Data Collection, Preparation, Labeling, and Input Coding - Output Coding - Post-Processing - Supervised Training Methods - Unsupervised Training Methods - Recurrent Neural Networks - A Plethora of Applications - Dealing with Limited Amounts of Data - Appendix A: The Feedforward Neural Network - Appendix B: Feature Saliency - Appendix C: Matlab Code for Various Neural Networks - Appendix D: Glossary of Terms - References - Index.

Mathukumalli Vidyasagar ... 488 pages - Publisher: Springer; 2nd edition (November, 2002) ...
Language: English - ISBN-10: 1852333731 - ISBN-13: 978-1852333737 ...

Learning and Generalization provides a formal mathematical theory for addressing intuitive questions such as: How does a machine learn a new concept on the basis of examples? • How can a neural network, after sufficient training, correctly predict the outcome of a previously unseen input? • How much training is required to achieve a specified level of accuracy in the prediction? • How can one identify the dynamical behaviour of a nonlinear control system by observing its input-output behaviour over a finite interval of time?

In its successful first edition, A Theory of Learning and Generalization was the first book to treat the problem of machine learning in conjunction with the theory of empirical processes, the latter being a well-established branch of probability theory. The treatment of both topics side-by-side leads to new insights, as well as to new results in both topics. This second edition extends and improves upon this material, covering new areas including: • Support vector machines. • Fat-shattering dimensions and applications to neural network learning. • Learning with dependent samples generated by a beta-mixing process. • Connections between system identification and learning theory. • Probabilistic solution of 'intractable problems' in robust control and matrix theory using randomized algorithm. Reflecting advancements in the field, solutions to some of the open problems posed in the first edition are presented, while new open problems have been added. Learning and Generalization (second edition) is essential reading for control and system theorists, neural network researchers, theoretical computer scientists and probabilist.

Louis H. Turcotte, H. B. Wilson ... 321 pages - Publisher: Prentice Hall; 1st edition (July, 1997) ...
Language: English - ISBN-10: 0137490607 - ISBN-13: 978-0137490608 ...

Focusing on physical applications in mechanics, the book's goal is to explore the benefits of computer usage in problem solving. Presents numerous example problems which demonstrate each program. Includes several thousand lines of carefully structured MATLAB code suitable for detailed study.

Peter Flach ... 409 pages - Publisher: Cambridge University Press; 1st edition (November, 2012) ... Language: English - ISBN-10: 1107422221 - ISBN-13: 978-1107422223 ...

As one of the most comprehensive machine learning texts around, this book does justice to the field's incredible richness, but without losing sight of the unifying principles. Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook.

Andrew Knight ... 216 pages - Publisher: Chapman and Hall/CRC; 1st edition (August, 1999) ...
Language: English - ISBN-10: 0849320399 - ISBN-13: 978-084932039 ...

MATLAB-the tremendously popular computation, numerical analysis, signal processing, data analysis, and graphical software package-allows virtually every scientist and engineer to make better and faster progress. As MATLAB's world-wide sales approach a half-million with an estimated four million users, it becomes a near necessity that professionals and students have a level of competence in its use. Until now, however, there has been no book that quickly and effectively introduces MATLAB's capabilities to new users and assists those with more experience down the path toward increasingly sophisticated work.

Basics of MATLAB and Beyond is just such a book. Its hands-on, tutorial approach gently takes new users by the hand and leads them to competence in all the fundamentals of MATLAB. Then, with equal effectiveness, it covers the advanced topics that lead to full, creative exploitation of MATLAB's awesome power. With this book, readers will: Solve more problems with MATLAB-and solve them faster * Create clearer, more beautiful graphics with control over every detail * Create their own MATLAB code * Share their work by exporting data and graphics to other applications * Develop graphical user interfaces. Based on the latest 5.x release, Basics of MATLAB and Beyond supplies both novice and experienced users the tools they need to gain proficiency, increase productivity, and ultimately have more fun with MATLAB.

Christian Blum, Günther R. Raidl ... 157 pages - Publisher: Springer; 1st edition (May, 2016) ...
Language: English - ISBN-10: 3319308823 - ISBN-13: 978-3319308821 ...

This book explains the most prominent and some promising new, general techniques that combine metaheuristics with other optimization methods. A first introductory chapter reviews the basic principles of local search, prominent metaheuristics, and tree search, dynamic programming, mixed integer linear programming, and constraint programming for combinatorial optimization purposes. The chapters that follow present five generally applicable hybridization strategies, with exemplary case studies on selected problems: incomplete solution representations and decoders; problem instance reduction; large neighborhood search; parallel non-independent construction of solutions within metaheuristics; and hybridization based on complete solution archives.

The authors are among the leading researchers in the hybridization of metaheuristics with other techniques for optimization, and their work reflects the broad shift to problem-oriented rather than algorithm-oriented approaches, enabling faster and more effective implementation in real-life applications. This hybridization is not restricted to different variants of metaheuristics but includes, for example, the combination of mathematical programming, dynamic programming, or constraint programming with metaheuristics, reflecting cross-fertilization in fields such as optimization, algorithmics, mathematical modeling, operations research, statistics, and simulation. The book is a valuable introduction and reference for researchers and graduate students in these domains.

A. Kaveh ... 373 pages -Publisher: Springer; (December, 2016) ... Language: English - ISBN-10: 3319480111 - ISBN-13: 978-3319480114.

The book presents recently developed efficient metaheuristic optimization algorithms and their applications for solving various optimization problems in civil engineering. The concepts can also be used for optimizing problems in mechanical and electrical engineering.

Gordon Filby ... 289 pages - Publisher: Springer; (September, 1998) ...
Language: English - ISBN-10: 354061253X - ISBN-13: 978-3540612537 ...

"Spreadsheets in Science and Engineering" shows scientists and engineers at all levels how to analyze, validate and calculate data and how the analytical and graphic capabilities of spreadsheet programs (ExcelR) can solve these tasks in their daily work. The examples on the CD-ROM accompanying the book include material of undergraduate to current research level in disciplines ranging from chemistry and chemical engineering to molecular biology and geology.

M. Asghar Bhatti ... 715 pages - Publisher: Springer; (June, 2000) ... Language: English - ISBN-10: 0387986316 - ISBN-13: 978-0387986319 ...

This introductory textbook adopts a practical and intuitive approach, rather than emphasizing mathematical rigor. Computationally oriented books in this area generally present algorithms alone, and expect readers to perform computations by hand, and are often written in traditional computer languages, such as Basic, Fortran or Pascal. This book, on the other hand, is the first text to use Mathematica to develop a thorough understanding of optimization algorithms, fully exploiting Mathematica's symbolic, numerical and graphic capabilities.

Fred W. Glover, Gary A. Kochenberger ... 570 pages - Publisher: Springer; 1st edition (January, 2003) ...
Language: English - ISBN-10: 1402072635 - ISBN-13: 978-1402072635 ...

This book provides both the research and practitioner communities with a comprehensive coverage of the metaheuristic methodologies that have proven to be successful in a wide variety of real-world problem settings. Moreover, it is these metaheuristic strategies that hold particular promise for success in the future. The various chapters serve as stand alone presentations giving both the necessary background underpinnings as well as practical guides for implementation.

Xin-She Yang, Zhihua Cui, Renbin Xiao, Amir Hossein Gandomi and Mehmet Karamanoglu ... 450 pages - Publisher: Elsevier; 1st edition (June, 2013) ... Language: English - ISBN-10: 1493301365 - ISBN-13: 978-1493301362 ... 

Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decades. Bio-inspired algorithms such as ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied in almost every area of science and engineering with a dramatic increase of number of relevant publications. This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses the latest and future trends in research directions. It can help new researchers to carry out timely research and inspire readers to develop new algorithms. With its impressive breadth and depth, this book will be useful for advanced undergraduate students, PhD students and lecturers in computer science, engineering and science as well as researchers and engineers. * Focuses on the introduction and analysis of key algorithms * Includes case studies for real-world applications * Contains a balance of theory and applications, so readers who are interested in either algorithm or applications will all benefit from this timely book.

Maurice Clerc, Bijaya Ketan Panigrahi, Yuhui Shi, Meng-Hiot Lim ... 
544 pages - Publisher: Springer;  (January, 2011) ... Language: English - ISBN-10: 3642173896 - ISBN-13: 978-3642173899.

From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more.  It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques.  In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume serves as a useful foundational as well as consolidatory state-of-art collection of articles in the field from various researchers around the globe.  It has a rich collection of contributions pertaining to the theoretical and empirical study of single and multi-objective variants of swarm intelligence based algorithms like particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), honey bee social foraging algorithms, and harmony search (HS).  With chapters describing various applications of SI techniques in real-world engineering problems, this handbook can be a valuable resource for researchers and practitioners, giving an in-depth flavor of what SI is capable of achieving.

Aboul Ella Hassanien, Eid Emary ... 228 pages - Publisher: CRC Press; (November, 2015) ... Language: English - ISBN-10: 1498741061 - ISBN-13: 978-1498741064.

Swarm Intelligence: Principles, Advances, and Applications delivers in-depth coverage of bat, artificial fish swarm, firefly, cuckoo search, flower pollination, artificial bee colony, wolf search, and gray wolf optimization algorithms. The book begins with a brief introduction to mathematical optimization, addressing basic concepts related to swarm intelligence, such as randomness, random walks, and chaos theory. The text then: * Describes the various swarm intelligence optimization methods, standardizing the variants, hybridizations, and algorithms whenever possible * Discusses variants that focus more on binary, discrete, constrained, adaptive, and chaotic versions of the swarm optimizers * Depicts real-world applications of the individual optimizers, emphasizing variable selection and fitness function design * Details the similarities, differences, weaknesses, and strengths of each swarm optimization method * Draws parallels between the operators and searching manners of the different algorithms. Swarm Intelligence: Principles, Advances, and Applications presents a comprehensive treatment of modern swarm intelligence optimization methods, complete with illustrative examples and an extendable MATLAB® package for feature selection in wrapper mode applied on different data sets with benchmarking using different evaluation criteria. The book provides beginners with a solid foundation of swarm intelligence fundamentals, and offers experts valuable insight into new directions and hybridizations.

Marco Dorigo, Mauro Birattari, Christian Blum, Maurice Clerc, Thomas Stützle, Alan Winfield ... 416 pages - Publisher: Springer; (October, 2008) ... Language: English - ISBN-10: 3540875263 - ISBN-13: 978-3540875260.

This book constitutes the refereed proceedings of the 6th International Workshop on Ant Colony Optimization and Swarm Intelligence, ANTS 2008, held in Brussels, Belgium, in September 2008. The 17 revised full papers, 24 revised short papers, and 10 extended abstracts presented were carefully reviewed and selected from 91 submissions. The papers cover theoretical and foundational aspects of computational intelligence and related disciplines with special focus on swarm intelligence and are devoted to behavioral models of social insects and new algorithmic approaches, empirical and theoretical research in swarm intelligence, applications such as ant colony optimization or particle swarm optimization, and theoretical and experimental research in swarm robotics systems.

The series of biannual international conferences “ANTS – International C- ference on Ant Colony Optimization and Swarm Intelligence”, now in its sixth edition, was started ten years ago, with the organization of ANTS’98. As some readers might recall, the first edition of ANTS was titled “ANTS’98 – From Ant Colonies to Artificial Ants: First International Workshop on Ant Colony Op- mization. ” In fact, at that time the focus was mainly on ant colony optimization (ACO), the first swarm intelligence algorithm to go beyond a pure scientific interest and to enter the realm of real-world applications. Interestingly, in the ten years after the first edition there has been a gr- ing interest not only for ACO, but for a number of other studies that belong more generally to the area of swarmintelligence. The rapid growth of the swarm intelligence field is attested by a number of indicators. First, the number of s- missions and participants to the ANTS conferences has steadily increased over the years. Second, a number of international conferences in computational - intelligence and related disciplines organize workshops on subjects such as swarm intelligence, ant algorithms, ant colony optimization, and particle swarm op- mization. Third, IEEE startedorganizing,in 2003, the IEEE SwarmIntelligence Symposium (in order to maintain unity in this growing field, we are currently establishing a cooperation agreement between IEEE SISandANTSsoastohave 1 IEEE SIS in odd years and ANTS in even years). Last, the Swarm Intelligence journal was born.

Avi Ostfeld ... 352 pages - Publisher: InTech; 1st edition (February, 2011) ...
Language: English - ISBN-10: N/A - ISBN-13: 978-9533071572 ...

Ants communicate information by leaving pheromone tracks. A moving ant leaves, in varying quantities, some pheromone on the ground to mark its way. While an isolated ant moves essentially at random, an ant encountering a previously laid trail is able to detect it and decide with high probability to follow it, thus reinforcing the track with its own pheromone. The collective behavior that emerges is thus a positive feedback: where the more the ants following a track, the more attractive that track becomes for being followed; thus the probability with which an ant chooses a path increases with the number of ants that previously chose the same path. This elementary ant's behavior inspired the development of ant colony optimization by Marco Dorigo in 1992, constructing a meta-heuristic stochastic combinatorial computational methodology belonging to a family of related meta-heuristic methods such as simulated annealing, Tabu search and genetic algorithms. This book covers in twenty chapters state of the art methods and applications of utilizing ant colony optimization algorithms. New methods and theory such as multi colony ant algorithm based upon a new pheromone arithmetic crossover and a repulsive operator, new findings on ant colony convergence, and a diversity of engineering and science applications from transportation, water resources, electrical and computer science disciplines are presented.

Justin Solomon ... 400 pages - Publisher: CRC Press; (July, 2015) ...
Language: English - ISBN-10: 1482251884 - ISBN-13: 978-1482251883 ... 

Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics presents a new approach to numerical analysis for modern computer scientists. Using examples from a broad base of computational tasks, including data processing, computational photography, and animation, the textbook introduces numerical modeling and algorithmic design from a practical standpoint and provides insight into the theoretical tools needed to support these skills.

The book covers a wide range of topics―from numerical linear algebra to optimization and differential equations―focusing on real-world motivation and unifying themes. It incorporates cases from computer science research and practice, accompanied by highlights from in-depth literature on each subtopic. Comprehensive end-of-chapter exercises encourage critical thinking and build students’ intuition while introducing extensions of the basic material.

The text is designed for advanced undergraduate and beginning graduate students in computer science and related fields with experience in calculus and linear algebra. For students with a background in discrete mathematics, the book includes some reminders of relevant continuous mathematical background.

Sergios Theodoridis ... 1062 pages - Publisher: Academic Press; 1st edition (April, 2015) ... Language: English - ISBN-10: 0128015225 - ISBN-13: 978-0128015223 ... 

This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches -which are based on optimization techniques – together with the Bayesian inference approach, whose essence lies in the use of a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts.The book builds carefully from the basic classical methods  to  the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for  different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as short courses on sparse modeling, deep learning, and probabilistic graphical models. All major classical techniques: Mean/Least-Squares regression and filtering, Kalman filtering, stochastic approximation and online learning, Bayesian classification, decision trees, logistic regression and boosting methods. * The latest trends: Sparsity, convex analysis and optimization, online distributed algorithms, learning in RKH spaces, Bayesian inference, graphical and hidden Markov models, particle filtering, deep learning, dictionary learning and latent variables modeling. * Case studies - protein folding prediction, optical character recognition, text authorship identification, fMRI data analysis, change point detection, hyperspectral image unmixing, target localization, channel equalization and echo cancellation, show how the theory can be applied. * MATLAB code for all the main algorithms are available on an accompanying website, enabling the reader to experiment with the code.

Gennadiy P. Nikishkov ... 402 pages - Publisher: Springer; (January 12, 2010) ...
Language: English - ISBN-10: 184882971X - ISBN-13: 978-1848829718 ...

The finite element method (FEM) is a computational technique for solving problems which are described by partial differential equations or which can be formulated as functional minimization. The FEM is commonly used in the design and development of products, especially where structural analysis is involved. The simple object model of the Java™ programming language lends itself to efficient implementation of FEM analysis.

Programming Finite Elements in Java™ teaches the reader FEM algorithms and their programming in Java™ through a single finite element Java™ program. The compact, simple code makes it straightforward to understand the algorithms and their implementation, thereby encouraging developers to extend the code to their own tasks. All of the main aspects of finite element techniques are considered: finite element solution;  generation of finite element meshes; and visualization of finite element models and results with Java 3D™.

The step-by-step presentation includes algorithm programming and code explanation at each point. Problems and exercises are provided for each chapter, with Java™ source code and problem data sets available from http://extras.springer.com/2010/978-1-84882-971-8.

Graduate students using the FEM will find the simple but detailed object-oriented programming methods presented in this textbook to be of great assistance in understanding the FEM, including mesh generation and visualization. Programming Finite Elements in Java™ will also be of interest to senior undergraduates doing special studies encompassing the FEM. Researchers and practicing engineers already familiar with the FEM but seeking an alternative approach will find this book readily suited to self study.

Ken Bluttman - 408 pages - Publisher: For Dummies; 4th edition (December, 2015) ...
Language: English - ISBN-10: 1119076781 - ISBN-13: 978-1119076780 ... 

Grab these Excel formulas and functions to make your life easier!: Are you intimidated by major financial choices, like which loan to get or how to grow your savings? Don't worry—we all are! But Excel Formulas & Functions For Dummies, 4th Edition can take some of the pain out of the data organization and analysis processes. This step-by-step reference sheds light on Microsoft Excel's 150 most useful functions, and offers detailed instructions on how to implement them. Additionally, each function is illustrated by helpful, real-world examples that show how they are used within a larger formula. To take your knowledge of Excel's functions a step further, 85 specialized functions are described in abbreviated form so you can use Excel to better support your decision-making process when securing a mortgage, buying a car, computing classroom grades, evaluating investment performance, and more.

Functions are predefined formulas that you can use to make data analysis a bit easier within the Microsoft Excel framework. Functions use specific values, called arguments, to calculate a variety of things, from simple sums and averages to more complicated loan payments. Explore the 150 most useful functions that help Microsoft Excel make your life easier * Access real-world examples of how functions fit into larger formulas * Discover 85 specialized functions, which are described in abbreviated form and take your knowledge of Excel to the next level * Understand how Microsoft Excel can help you make key decisions, such as whether to go with a 15-year or 30-year mortgage. Excel Formulas & Functions For Dummies, 4th Edition brings order to chaotic data—and helps you make decisions with confidence!

Contact Form

Name

Email *

Message *

Powered by Blogger.