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MATLAB for Engineers is intended for use in the first-year or introductory course in Engineering and Computer Science departments. It is also suitable for readers interested in learning MATLAB. ¿ With a hands-on approach and focus on problem solving, this introduction to the powerful MATLAB computing language is designed for students with only a basic college algebra background. Numerous examples are drawn from a range of engineering disciplines, demonstrating MATLAB’s applications to a broad variety of problems. ¿ Teaching and Learning Experience This program will provide a better teaching and learning experience–for you and your students. Customize your Course with ESource: Instructors can adopt this title as is, or use the ESource website to select the chapters they need, in the sequence they want. Introduce MATLAB Clearly: Three well-organized sections gets students started with MATLAB, introduce students to programming, and demonstrate more advanced programming techniques. Reinforce Core Concepts with Hands-on Activities: Examples and exercises demonstrate how MATLABcan be used to solve a variety of engineering problems. Keep Your Course Current: Significant changes were introduced in version MATLAB 2012b, including the introduction of MATLAB 8 which has a redesigned user-interface. The changes in this edition reflect these software updates. Support Learning with Instructor Resources: A variety of resources are available to help to enhance your course.

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 applicationsProblem-based approach with many examples from neuroscience and cognitive psychology using real dataIllustrated in full color throughout Careful tutorial approach, by authors who are award-winning educators with strong teaching experience

Plot graphs, solve equations, and write code in a flash! If you work in a STEM field, chances are you'll be using MATLAB on a daily basis. MATLAB is a popular and powerful computational tool and this book provides everything you need to start manipulating and plotting your data. MATLAB has rapidly become the premier data tool, and MATLAB For Dummies is a comprehensive guide to the fundamentals. MATLAB For Dummies guides you through this complex computational language from installation to visualization to automation. Learn MATLAB's language fundamentals including syntax, operators, and data types Understand how to use the most important window in MATLAB – the Command Window Get the basics of linear algebra to get up and running with vectors, matrices, and hyperspace Automate your work with programming scripts and functions Plot graphs in 2D and 3D to visualize your data Includes a handy guide for MATLAB's functions and plotting routines MATLAB is an essential part of the analysis arsenal and MATLAB For Dummies provides clear, thorough guidance to get the most out of your data.

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 LearnUse MATLAB for deep learningDiscover neural networks and multi-layer neural networksWork with convolution and pooling layersBuild a MNIST example with these layersWho This Book Is ForThose who want to learn deep learning using MATLAB. Some MATLAB experience may be useful.

Harness the power of MATLAB to resolve a wide range of machine learning challenges. This book provides a series of examples of technologies critical to machine learning. Each example solves a real-world problem. All code in MATLAB Machine Learning Recipes:  A Problem-Solution Approach is executable. The toolbox that the code uses provides a complete set of functions needed to implement all aspects of machine learning. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow the reader to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more.What you'll learn:How to write code for machine learning, adaptive control and estimation using MATLABHow these three areas complement each otherHow these three areas are needed for robust machine learning applicationsHow to use MATLAB graphics and visualization tools for machine learningHow to code real world examples in MATLAB for major applications of machine learning in big data Who is this book for: The primary audiences are engineers, data scientists and students wanting a comprehensive and code cookbook rich in examples on machine learning using MATLAB.

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 applicationsProblem-based approach with many examples from neuroscience and cognitive psychology using real dataIllustrated in full color throughout Careful tutorial approach, by authors who are award-winning educators with strong teaching experience

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 LearnUse MATLAB for deep learningDiscover neural networks and multi-layer neural networksWork with convolution and pooling layersBuild a MNIST example with these layersWho This Book Is ForThose who want to learn deep learning using MATLAB. Some MATLAB experience may be useful.

MATLAB By Example guides the reader through each step of writing MATLAB programs. The book assumes no previous programming experience on the part of the reader, and uses multiple examples in clear language to introduce concepts and practical tools. Straightforward and detailed instructions allow beginners to learn and develop their MATLAB skills quickly. The book consists of ten chapters, discussing in detail the integrated development environment (IDE), scalars, vectors, arrays, adopting structured programming style using functions and recursive functions, control flow, debugging, profiling, and structures. A chapter also describes Symbolic Math Toolbox, teaching readers how to solve algebraic equations, differentiation, integration, differential equations, and Laplace and Fourier transforms. Containing hundreds of examples illustrated using screen shots, hundreds of exercises, and three projects, this book can be used to complement coursework or as a self-study book, and can be used as a textbook in universities, colleges and high schools.No programming experience necessary to learn MATLABExamples with screenshots and plentiful exercises throughout help make MATLAB easy to understandProjects enable readers to write long MATLAB programs, and take the first step toward being a professional MATLAB programmer

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Designed for the newest version of the popular MATLAB software program, MATLAB: An Introduction with Applications, 3/e requires no previous knowledge of computer programming. The first chapter describes basic features of the program and shows how to use it in simple arithmetic operations with scalars. The next two chapters focus on the topic of arrays (the basis of MATLAB), while the remaining text covers a wide range of other applications. Computer screens, tutorials, samples, and homework questions in math, science, and engineering, provide the student with the practical hands-on experience needed for total proficiency.    

Master the MATLAB technical programming language with MATLAB PROGRAMMING FOR ENGINEERS, 5E! Emphasizing problem-solving skills throughout, this latest edition of Chapman's successful book shows you how to write clean, efficient, and well-documented programs, while simultaneously introducing you to many of the practical functions of MATLAB.

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MATLAB for Engineers, 2e is ideal for Freshman or Introductory courses in Engineering and Computer Science. With a hands-on approach and focus on problem solving, this introduction to the powerful MATLAB computing language is designed for students with only a basic college algebra background. Numerous examples are drawn from a range of engineering disciplines, demonstrating MATLAB’s applications to a broad variety of problems. Note: This book is included in Prentice Hall’s ESource series. ESource allows professors to select the content appropriate for their freshman/first-year engineering course. Professors can adopt the published manuals as is or use ESource’s website www.prenhall.com/esource to view and select the chapters they need, in the sequence they want. The option to add their own material or copyrighted

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Harness the power of MATLAB to resolve a wide range of machine learning challenges. This book provides a series of examples of technologies critical to machine learning. Each example solves a real-world problem. All code in MATLAB Machine Learning Recipes:  A Problem-Solution Approach is executable. The toolbox that the code uses provides a complete set of functions needed to implement all aspects of machine learning. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow the reader to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more.What you'll learn:How to write code for machine learning, adaptive control and estimation using MATLABHow these three areas complement each otherHow these three areas are needed for robust machine learning applicationsHow to use MATLAB graphics and visualization tools for machine learningHow to code real world examples in MATLAB for major applications of machine learning in big data Who is this book for: The primary audiences are engineers, data scientists and students wanting a comprehensive and code cookbook rich in examples on machine learning using MATLAB.

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MATLAB is an interactive system for numerical computation that is widely used for teaching and research in industry and academia. It provides a modern programming language and problem solving environment, with powerful data structures, customizable graphics, and easy-to-use editing and debugging tools. This second edition of MATLAB Guide completely revises and updates the best-selling first edition and is more than 30% longer. The book remains a lively, concise introduction to the most popular and important features of MATLAB 7 and the Symbolic Math Toolbox.