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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

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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.

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.

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

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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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.

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MATLAB for Neuroscientists: An Introduction to Scientific Computing in MATLAB is the first comprehensive teaching resource and textbook for the teaching of MATLAB in the Neurosciences and in Psychology. MATLAB is unique in that it can be used to learn the entire empirical and experimental process, including stimulus generation, experimental control, data collection, data analysis and modeling. Thus a wide variety of computational problems can be addressed in a single programming environment. The idea is to empower advanced undergraduates and beginning graduate students by allowing them to design and implement their own analytical tools. As students advance in their research careers, they will have achieved the fluency required to understand and adapt more specialized tools as opposed to treating them as "black boxes". Virtually all computational approaches in the book are covered by using genuine experimental data that are either collected as part of the lab project or were collected in the labs of the authors, providing the casual student with the look and feel of real data. In some cases, published data from classical papers are used to illustrate important concepts, giving students a computational understanding of critically important research.The first comprehensive textbook on MATLAB with a focus for its application in neuroscienceProblem based educational approach with many examples from neuroscience and cognitive psychology using real dataAuthors are award-winning educators with strong teaching experience

MATLAB for Engineering Applications is a simple, concise book designed to be useful for beginners and to be kept as a reference. MATLAB is a globally available standard computational tool for engineers and scientists. The terminology, syntax, and the use of the programming language are well defined, and the organization of the material makes it easy to locate information and navigate through the textbook. The text covers all the major capabilities of MATLAB that are useful for beginning students. The text consists of 11 chapters. The first five chapters constitute a basic course in MATLAB. The remaining six chapters are independent of each other and cover more advanced applications of MATLAB, the Control Systems tool- box, Simulink, and the Symbolic Math toolbox.

Emphasizing problem-solving skills throughout this very successful book, Stephen Chapman introduces the MATLAB language and shows how to use it to solve typical technical problems. The book teaches MATLAB as a technical programming language showing students how to write clean, efficient, and well-documented programs. It makes no pretense at being a complete description of all of MATLAB's hundreds of functions. Instead, it teaches students how to locate any desired function with MATLAB's extensive on line help facilities. Overall, students develop problem-solving skills and are equipped for future courses and careers using the power of MATLAB.

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.Need to Learn MATLAB? Problem SOLVED! Get started using MATLAB right away with help from this hands-on guide. MATLAB Demystified offers an effective and enlightening method for learning how to get the most out this powerful computational mathematics tool.  Using an easy-to-follow format, this book explains the basics of MATLAB up front. You'll find out how to plot functions, solve algebraic equations, and compute integrals. You'll also learn how to solve differential equations, generate numerical solutions of ODEs, and work with special functions. Packed with hundreds of sample equations and explained solutions, and featuring end-of-chapter quizzes and a final exam, this book will teach you MATLAB essentials in no time at all.This self-teaching guide offers:The quickest way to get up and running on MATLABHundreds of worked examples with solutionsCoverage of MATLAB 7A quiz at the end of each chapter to reinforce learning and pinpoint weaknessesA final exam at the end of the bookA time-saving approach to performing better on homework or on the jobSimple enough for a beginner, but challenging enough for an advanced user, MATLAB Demystified is your shortcut to computational precision.

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MATLAB® is used for a wide range of applications in geosciences, such as image processing in remote sensing, the generation and processing of digital elevation models and the analysis of time series. This book introduces methods of data analysis in geosciences using MATLAB, such as basic statistics for univariate, bivariate and multivariate datasets, time-series analysis, signal processing, the analysis of spatial and directional data and image analysis. The revised and updated Fourth Edition includes sixteen new sections and most chapters have greatly been expanded so that they now include a step by step discussion of all methods before demonstrating the methods with MATLAB functions. New sections include: Array Manipulation; Control Flow; Creating Graphical User Interfaces; Hypothesis Testing; Kolmogorov-Smirnov Test; Mann-Whitney Test; Ansari-Bradley Test; Detecting Abrupt Transitions in Time Series; Exporting 3D Graphics to Create Interactive Documents; Importing, Processing and Exporting LANDSAT Images; Importing and Georeferencing TERRA ASTER Images; Processing and Exporting EO-1 Hyperion Images; Image Enhancement; Correction and Rectification; Shape-Based Object Detection in Images; Discriminant Analysis; and Multiple Linear Regression. The text includes numerous examples demonstrating how MATLAB can be used on data sets from earth sciences. The book’s supplementary electronic material (available online through Springer Link) includes recipes that include all the MATLAB commands featured in the book and the example data.

Notable author Katsuhiko Ogata presents the only new book available to discuss, in sufficient detail, the details of MATLAB® materials needed to solve many analysis and design problems associated with control systems. Complements a large number of examples with in-depth explanations, encouraging complete understanding of the MATLAB approach to solving problems. Distills the large volume of MATLAB information available to focus on those materials needed to study analysis and design problems of deterministic, continuous-time control systems. Covers conventional control systems such as transient response, root locus, frequency response analyses and designs; analysis and design problems associated with state space formulation of control systems; and useful MATLAB approaches to solve optimization problems. A useful self-study guide for practicing control engineers.