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MATLAB Deep Learning
by Phil KimThis book consists of six chapters, which can be grouped into three subjects. The first subject is Machine Learning and takes place in Chapter 1. Deep Learning stems from Machine Learning. This implies that if you want to understand the essence of Deep Learning, you have to know the philosophy behind Machine Learning to some extent. Chapter 1 starts with the relationship between Machine Learning and Deep Learning, followed by problem solving strategies and fundamental limitations of Machine Learning. The detailed techniques are not introduced yet. Instead, fundamental concepts that applies to both the neural network and Deep Learning will be covered. The second subject is artificial neural network. Chapters 2-4 focuses on this subject. As Deep Learning is a type of Machine Learning that employs a neural network, the neural network is inseparable from Deep Learning. Chapter 2 starts with the fundamentals of the neural network: principles of its operation, architecture, and learning rules. It also provides the reason that the simple single-layer architecture evolved to the complex multi-layer architecture. Chapter 3 presents the backpropagation algorithm, which is an important and representative learning rule of the neural network and also employed in Deep Learning. This chapter explains how cost functions and learning rules are related and which cost functions are widely employed in Deep Learning. Chapter 4 introduces how to apply the neural network to classification problems. We have allocated a separate section for classification because it is currently the most prevailing application of Machine Learning. For example, image recognition, one of the primary applications of Deep Learning, is a classification problem. The third topic is Deep Learning. It is the main topic of this book as well. Deep Learning is covered in Chapters 5 and 6. Chapter 5 introduces the drivers that enables Deep Learning to yield excellent performance. For a better understanding, it starts with the history of barriers and solutions of Deep Learning. Chapter 6 covers the convolution neural network, which is representative of Deep Learning techniques. The convolution neural network is second-to-none in terms of image recognition. This chapter starts with an introduction of the basic concept and architecture of the convolution neural network as it compares with the previous image recognition algorithms. It is followed by an explanation of the roles and operations of the convolution layer and pooling layer, which act as essential components of the convolution neural network. The chapter concludes with an example of digit image recognition using the convolution neural network and investigates the evolution of the image throughout the layers.
MATLAB For Dummies
by John Paul Mueller Jim SizemoreGo from total MATLAB newbie to plotting graphs and solving equations in a flash! MATLAB is one of the most powerful and commonly used tools in the STEM field. But did you know it doesn’t take an advanced degree or a ton of computer experience to learn it? MATLAB For Dummies is the roadmap you’ve been looking for to simplify and explain this feature-filled tool. This handy reference walks you through every step of the way as you learn the MATLAB language and environment inside-and-out. Starting with straightforward basics before moving on to more advanced material like Live Functions and Live Scripts, this easy-to-read guide shows you how to make your way around MATLAB with screenshots and newly updated procedures. It includes: A comprehensive introduction to installing MATLAB, using its interface, and creating and saving your first file Fully updated to include the 2020 and 2021 updates to MATLAB, with all-new screenshots and up-to-date procedures Enhanced debugging procedures and use of the Symbolic Math Toolbox Brand new instruction on working with Live Scripts and Live Functions, designing classes, creating apps, and building projects Intuitive walkthroughs for MATLAB’s advanced features, including importing and exporting data and publishing your work Perfect for STEM students and new professionals ready to master one of the most powerful tools in the fields of engineering, mathematics, and computing, MATLAB For Dummies is the simplest way to go from complete newbie to power user faster than you would have thought possible.
MATLAB Graphics and Data Visualization Cookbook
by Nivedita Majumdar Swapnonil Banerjee"MATLAB Graphics and Data Visualization Cookbook" will serve as your handbook in recipe format with ample screenshots. Each independent recipe will help you in achieving target-oriented solutions to your problems with concise explanation. For those who are already using MATLAB for their computational needs but need to also harness its powerful visualization capabilities.
MATLAB Lessons, Examples, and Exercises: A Tutorial for Beginners and Experts
by Mehdi Rahmani-AndebiliMATLAB Lessons, Examples, and Exercises: A Tutorial for Beginners and Experts is a book for anyone interested in learning MATLAB, a popular programming language used in mathematics, engineering, and science. Whether you’re a student, instructor, engineer, or technical professional, this book provides easy-to-follow lessons, examples, and exercises in each section of every chapter, emphasizing writing and executing code to help you become proficient in programming with MATLAB. Different colors make the code, outputs, and program descriptions more straightforward to read to improve reader comprehension. The book covers all the essential functions of MATLAB that are needed in math, engineering, and science, and it explains the math behind each function so you can apply them to solve real-world problems. Whether you’re new to programming or an expert, this book offers clear explanations, diverse examples, and hands-on exercises to help you improve your MATLAB programming skills and understand how to use MATLAB in various fields.
MATLAB Machine Learning
by Stephanie Thomas Michael PaluszekThis 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.
MATLAB Machine Learning Recipes: A Problem-Solution Approach
by Stephanie Thomas Michael PaluszekHarness 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 Machine Learning Recipes: A Problem-Solution Approach
by Stephanie Thomas Michael PaluszekHarness the power of MATLAB to resolve a wide range of machine learning challenges. This new and updated third edition provides examples of technologies critical to machine learning. Each example solves a real-world problem, and all code provided is executable. You can easily look up a particular problem and follow the steps in the solution.This book has something for everyone interested in machine learning. It also has material that will allow those with an interest in other technology areas to see how machine learning and MATLAB can help them solve problems in their areas of expertise. The chapter on data representation and MATLAB graphics includes new data types and additional graphics. Chapters on fuzzy logic, simple neural nets, and autonomous driving have new examples added. And there is a new chapter on spacecraft attitude determination using neural nets. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow you to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more.What You Will LearnWrite code for machine learning, adaptive control, and estimation using MATLABUse MATLAB graphics and visualization tools for machine learningBecome familiar with neural netsBuild expert systemsUnderstand adaptive controlGain knowledge of Kalman FiltersWho This Book Is ForSoftware engineers, control engineers, university faculty, undergraduate and graduate students, hobbyists.
MATLAB Programming with Applications for Engineers
by Stephen J. ChapmanThis textbook seeks to simultaneously teach MATLAB as a technical programming language while introducing the student to many of the practical functions that make solving problems in MATLAB so much easier than in other languages. It provides a complete introduction to the fundamentals of good procedural programming and aids students in developing good design habits that will serve them well in any other language that they may pick up later.
MATLAB Recipes
by Stephanie Thomas Michael PaluszekLearn from state-of-the-art examples in robotics, motors, detection filters, chemical processes, aircraft, and spacecraft. MATLAB Recipes: A Problem-Solution Approach is a practical reference for industry engineers using MATLAB to solve everyday problems. With this book you will review contemporary MATLAB coding including the latest language features and use MATLAB as a software development environment including code organization, GUI development, and algorithm design and testing. This book provides practical guidance for using MATLAB to build a body of code you can turn to time and again for solving technical problems in your line of work. Develop algorithms, test them, visualize the results, and pass the code along to others to create a functional code base for your firm. What you'll learn Learn how to build industrial-strength toolboxes Move beyond a folder of scripts and create well-organized, reusable MATLAB code modules Leverage MATLAB as an IDE and not just a programming language Build a functional code base for your company or department Create your own GUIs for repeatable workflows Who this book is for This book is written for engineers and scientists who use MATLAB on a regular basis and who want to take their coding to a higher level, i. e. people who want to make commercial-quality MATLAB toolboxes. This book may be used by students who are required to use MATLAB for their courses and projects as well as professionals who use MATLAB to solve problems on the job. Table of Contents Part I: Coding in MATLAB 1. Coding Basics 2. MATLAB Style 3. Visualization 4. Interactive Graphics 5. Testing and Debugging Part II: Applications 6. The Double Integrator 7. Robotics 8. Electrical Motor 9. Fault Detection 10. Chemical Processes 11. Aircraft 12. Spacecraft
MATLAB Recipes: A Problem-Solution Approach
by Stephanie Thomas Michael PaluszekLearn from state-of-the-art examples in robotics, motors, detection filters, chemical processes, aircraft, and spacecraft. With this book you will review contemporary MATLAB coding including the latest MATLAB language features and use MATLAB as a software development environment including code organization, GUI development, and algorithm design and testing. Features now covered include the new graph and digraph classes for charts and networks; interactive documents that combine text, code, and output; a new development environment for building apps; locally defined functions in scripts; automatic expansion of dimensions; tall arrays for big data; the new string type; new functions to encode/decode JSON; handling non-English languages; the new class architecture; the Mocking framework; an engine API for Java; the cloud-based MATLAB desktop; the memoize function; and heatmap charts. MATLAB Recipes: A Problem-Solution Approach, Second Edition provides practical, hands-on code snippets and guidance for using MATLAB to build a body of code you can turn to time and again for solving technical problems in your work. Develop algorithms, test them, visualize the results, and pass the code along to others to create a functional code base for your firm. What You Will Learn Get up to date with the latest MATLAB up to and including MATLAB 2020bCode in MATLAB Write applications in MATLAB Build your own toolbox of MATLAB code to increase your efficiency and effectiveness Who This Book Is For Engineers, data scientists, and students wanting a book rich in examples using MATLAB.
MATLAB Roadmap to Applications: Volume I Fundamental
by Yi Chen Long HuangThis open access book presents a comprehensive guide to MATLAB programming, catering to students, engineers, and researchers seeking to harness MATLAB as a powerful tool for their work. The text meticulously covers fundamental concepts, progressing from basic elements such as types and operators to more complex structures like arrays and matrices. It elucidates key programming constructs including selection statements, loop structures, scripts, and functions, providing readers with a solid foundation in MATLAB programming. The book's structure is carefully crafted to facilitate step-by-step learning, with each chapter building upon previous knowledge. Abundant examples and exercises reinforce understanding, while dedicated sections on data visualisation, algorithm development, and practical applications in engineering, science, and finance demonstrate MATLAB's versatility across disciplines. A distinguishing feature of this volume is its inclusion of laboratory work and coursework, allowing readers to apply theoretical concepts to real-world scenarios. This hands-on approach enhances the learning experience and prepares users for practical implementation of MATLAB in their respective fields. In the current era of artificial intelligence, this book serves as an essential resource for those seeking to leverage MATLAB's capabilities. It not only equips readers with programming skills but also illustrates how MATLAB can be integrated into cutting-edge research and industry applications.
MATLAB and Simulink Crash Course for Engineers
by Eklas HossainMATLAB and Simulink Crash Course for Engineers is a reader-friendly introductory guide to the features, functions, and applications of MATLAB and Simulink. The book provides readers with real-world examples, exercises, and applications, and offers highly illustrated, step-by-step demonstrations of techniques for the modelling and simulation of complex systems. MATLAB coverage includes vectors and matrices, programs and functions, complex numbers, visualization, solving equations, numerical methods, optimization problems, and graphical user interfaces. The Simulink coverage includes commonly used Simulink blocks, control system simulation, electrical circuit analysis, electric power systems, power electronics, and renewable energy technology. This powerful tutorial is a great resource for students, engineers, and other busy technical professionals who need to quickly acquire a solid understanding of MATLAB and Simulink.
MATLAB and Simulink in Action: Programming, Scientific Computing and Simulation
by Dingyü Xue Feng PanThe textbook is intended for teaching MATLAB language and its applications. The book is composed of three parts: MATLAB programming, scientific computing with MATLAB, and system simulation with Simulink. Since MATLAB is widely used in all fields of science and engineering, a good introduction to the language can not only help students learn how to use it to solve practical problems, but also provide them with the skills to use MATLAB independently in their later courses and research. The three parts of the book are well-balanced and tailored to the needs of engineering students, and the mathematical problems commonly encountered in engineering can be easily solved using MATLAB. This textbook is suitable for undergraduate and graduate students majoring in science and engineering.
MATLAB for Brain and Cognitive Scientists
by Mike X CohenAn introduction to a popular programming language for neuroscience research, taking the reader from beginning to intermediate and advanced levels of MATLAB programming.MATLAB is one of the most popular programming languages for neuroscience and psychology research. Its balance of usability, visualization, and widespread use makes it one of the most powerful tools in a scientist's toolbox. In this book, Mike Cohen teaches brain scientists how to program in MATLAB, with a focus on applications most commonly used in neuroscience and psychology. Although most MATLAB tutorials will abandon users at the beginner's level, leaving them to sink or swim, MATLAB for Brain and Cognitive Scientists takes readers from beginning to intermediate and advanced levels of MATLAB programming, helping them gain real expertise in applications that they will use in their work.The book offers a mix of instructive text and rigorous explanations of MATLAB code along with programming tips and tricks. The goal is to teach the reader how to program data analyses in neuroscience and psychology. Readers will learn not only how to but also how not to program, with examples of bad code that they are invited to correct or improve. Chapters end with exercises that test and develop the skills taught in each chapter. Interviews with neuroscientists and cognitive scientists who have made significant contributions their field using MATLAB appear throughout the book. MATLAB for Brain and Cognitive Scientists is an essential resource for both students and instructors, in the classroom or for independent study.
MATLAB for Engineering and the Life Sciences (Synthesis Lectures on Engineering, Science, and Technology)
by Joe TranquilloThis book is a self-guided tour of MATLAB for engineers and life scientists. It introduces the most commonly used programming techniques through biologically inspired examples. Although the text is written for undergraduates, graduate students and academics, as well as those in industry, will find value in learning MATLAB. The book takes the emphasis off of learning syntax so that the reader can focus more on algorithmic thinking. Although it is not assumed that the reader has taken differential equations or a linear algebra class, there are short introductions to many of these concepts. Following a short history of computing, the MATLAB environment is introduced. Next, vectors and matrices are discussed, followed by matrix-vector operations. The core programming elements of MATLAB are introduced in three successive chapters on scripts, loops, and conditional logic. The last three chapters outline how to manage the input and output of data, create professional quality graphics and find and use MATLAB toolboxes. Throughout, biomedical and life science examples are used to illustrate MATLAB's capabilities.
MATLAB for Neuroscientists: An Introduction to Scientific Computing in MATLAB
by Pascal Wallisch Michael E. Lusignan Marc D. Benayoun Tanya I. Baker Adam Seth Dickey Nicholas G. HatsopoulosMATLAB 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.
MATLAB for Psychologists
by Alessandro Soranzo Mauro Borgo Massimo GrassiThe matrix laboratory interactive computing environment--MATLAB--has brought creativity to research in diverse disciplines, particularly in designing and programming experiments. More commonly used in mathematics and the sciences, it also lends itself to a variety of applications across the field of psychology. For the novice looking to use it in experimental psychology research, though, becoming familiar with MATLAB can be a daunting task. MATLAB for Psychologists expertly guides readers through the component steps, skills, and operations of the software, with plentiful graphics and examples to match the reader's comfort level. Using an extended illustration, this concise volume explains the program's usefulness at any point in an experiment, without the limits imposed by other types of software. And the authors demonstrate the responsiveness of MATLAB to the individual's research needs, whether the task is programming experiments, creating sensory stimuli, running simulations, or calculating statistics for data analysis. Key features of the coverage: Thinking in a matrix way.Handling and plotting data.Guidelines for improved programming, sound, and imaging.Statistical analysis and signal detection theory indexes.The Graphical User Interface.The Psychophysics Toolbox.MATLAB for Psychologists serves a wide audience of advanced undergraduate and graduate level psychology students, professors, and researchers as well as lab technicians involved in programming psychology experiments.
MATLAB for Psychologists
by Alessandro Soranzo Mauro Borgo Massimo Grassi Luca BattagliniThe second edition of this textbook provides a comprehensive and detailed overview of MATLAB and specific tools for creating experiments and analysing data in psychology. In addition to an enhanced focus on connections with external devices and writing experiments, all chapters have been thoroughly revised and updated to provide the latest information and examples compatible with the most recent versions of MATLAB. All scripts have been tested to ensure a reliable and exact response. In addition, the book provides detailed examples of classic experiments (e.g., the Posner task) as well as recommendations for structuring and implementing ad hoc experiments. Each chapter is accompanied by several illustrations, examples, and code to match every reader's expertise and comfort level. This concise volume demonstrates MATLAB’s responsiveness to individuals’ research needs, whether the task is programming experiments, creating sensory stimuli, running simulations, or calculating statistics for data analysis. Key areas of coverage include: Thinking in a matrix way. Handling and plotting data. Guidelines for improved programming, sound, and imaging. Statistical analysis and signal detection theory. Psychophysics Toolbox and its use in connection with external devices. MATLAB for Psychologists, Second Edition, serves a wide audience of advanced undergraduate and graduate level psychology students, professors, and researchers as well as lab technicians and other professionals involved in programming psychology experiments.
MATLAB und Simulink Schnellkurs für Ingenieure
by Eklas HossainMATLAB und Simulink Schnellkurs für Ingenieure ist ein benutzerfreundlicher Einführungsführer zu den Funktionen und Anwendungen von MATLAB und Simulink. Das Buch bietet Lesern praxisnahe Beispiele, Übungen und Anwendungen und zeigt hochillustrierte, schrittweise Demonstrationen von Techniken für die Modellierung und Simulation komplexer Systeme. Die MATLAB-Abdeckung umfasst Vektoren und Matrizen, Programme und Funktionen, komplexe Zahlen, Visualisierung, Lösung von Gleichungen, numerische Methoden, Optimierungsprobleme und grafische Benutzeroberflächen. Die Simulink-Abdeckung umfasst häufig verwendete Simulink-Blöcke, Simulation von Regelungssystemen, Analyse elektrischer Schaltungen, elektrische Energiesysteme, Leistungselektronik und erneuerbare Energietechnologien. Dieses leistungsstarke Tutorial ist eine ausgezeichnete Ressource für Studenten, Ingenieure und andere geschäftige technische Fachleute, die schnell ein solides Verständnis von MATLAB und Simulink erlangen müssen.
MATLAB® Recipes for Earth Sciences (Springer Textbooks in Earth Sciences, Geography and Environment)
by Martin H. TrauthMATLAB® is used in a wide range of geoscientific applications, such as for image processing in remote sensing, for generating and processing digital elevation models, and for analyzing time series. This book introduces methods of data analysis in the earth sciences using MATLAB, such as basic statistics for univariate, bivariate, and multivariate data sets, time series analysis, signal processing, spatial and directional data analysis, and image analysis. The text includes numerous examples demonstrating how MATLAB can be used on data sets from the earth sciences. The supplementary electronic material (available online through Springer Link) contains recipes that include all the MATLAB commands featured in the book and example data.
MATLAB® Recipes for Earth Sciences: Matlab® And Design Recipes For Earth Sciences (Springer Textbooks in Earth Sciences, Geography and Environment)
by Martin H. TrauthMATLAB® is used in a wide range of geoscientific applications, e.g. for image processing in remote sensing, for creating and processing digital elevation models, and for analyzing time series. This book introduces readers to MATLAB-based data analysis methods used in the geosciences, including 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 Fifth Edition includes seven new sections, and the majority of the chapters have been rewritten and significantly expanded. New sections include error analysis, the problem of classical linear regression of log-transformed data, aligning stratigraphic sequences, the Normalized Difference Vegetation Index, Aitchison’s log-ratio transformation, graphical representation of spherical data, and statistics of spherical data. The book also includes numerous examples demonstrating how MATLAB can be used on datasets from the earth sciences. The supplementary electronic material (available online through SpringerLink) contains recipes that include all the MATLAB commands featured in the book and the sample data.
MATLAB® for Brain-Computer Interface Systems: Computation and Data Processing
by Sanjiban Sekhar Roy Faridoddin ShariatyThe book extensively explores Brain-Computer Interfaces (BCIs), emphasizing both the theoretical foundations and practical applications within this rapidly advancing field. It provides a thorough coverage of BCI fundamentals and practical implementation using MATLAB®. It begins with an introduction, covering the history of BCIs, components, and the pivotal role MATLAB® plays in their development. The book explores various aspects such as signal processing, data acquisition, rapid prototyping, machine learning, and real-time data processing, all within the MATLAB® environment. Additionally, it delves into the community and support available, along with open-source BCI toolboxes and integration with external devices. Moving forward, the book dives into the fundamentals of BCIs, including their definition, applications, principles, and components. It covers different types of brain signals utilized in BCI systems and the challenges involved in their design, such as signal reliability, userfriendliness, privacy, and regulatory issues. It discusses their principles, implementation in MATLAB®, and practical considerations for training and evaluating classification models. Finally, the book concludes with real-world case studies and practical examples, demonstrating the application of MATLAB® in BCI projects.This book is an essential reading for researchers, engineers, students, and practitioners seeking to explore the fascinating intersection of neuroscience, signal processing, and machine learning through MATLAB-based BCI development.
MATLAB® meets MicroPython: Mit MATLAB® Mikrocontroller nutzen (essentials)
by Armin RohnenDieses essential behandelt die Verknüpfung von MicroPython betriebenen Mikrocontroller mit MATLAB®. Anhand eines Praxisbeispiels werden die Aspekte der Planung, der elektronischen Umsetzung, der Programmierung in MicroPython, die Programmierung in MATLAB® und die Erstellung einer graphischen Oberfläche handelt.
MATLAB®-Rezepte für die Geowissenschaften
by Martin H. TrauthTrauth, Martin H.MATLAB® - Rezepte für Geowissenschaften, 1. deutschsprachige Auflage, basierend auf der korrigierten 5. englischsprachigen AuflageMATLAB® wird in einer Vielzahl von geowissenschaftlichen Anwendungen eingesetzt, z.B. zur Bildverarbeitung in der Fernerkundung, zur Erzeugung und Verarbeitung digitaler Höhenmodelle und zur Analyse von Zeitreihen. Dieses Buch führt in Methoden der Datenanalyse in den Geowissenschaften mit MATLAB ein, wie z.B. grundlegende Statistik für univariate, bivariate und multivariate Datensätze, Zeitreihenanalyse, Signalverarbeitung, die Analyse räumlicher und gerichteter Daten und Bildanalyse. Der Text enthält zahlreiche Beispiele, die zeigen, wie MATLAB auf Datensätze aus den Geowissenschaften angewendet werden kann. Das ergänzende elektronische Material des Buches (online verfügbar über Springer Link) enthält Rezepte, die alle im Buch vorgestellten MATLAB-Befehle und die Beispieldaten enthalten. Das Buch soll Student:innen, Doktorand:innen, Postdoktorand:innen und Fachleuten helfen, schnelle Lösungen für gängige Datenanalyseprobleme in den Geowissenschaften zu finden.SystemanforderungenBenutzer:innen dieses Buches benötigen die MATLAB®-Software, die für Windows, macOS und Linux verfügbar ist. Die M-Files und Beispieldaten, die online über Springer Link verfügbar sind, sollten auf allen Plattformen laufen, ohne dass eine Modifikation erforderlich ist. Für diese Ausgabe haben wir MATLAB Version 9.11 (Release 2021b), die Bioinformatics Toolbox Version 4.15.2, die Image Processing Toolbox Version 11.4, die Mapping Toolbox Version 5.2, die Signal Processing Toolbox Version 8.7, Simulink 3D Animation Version 9.3, die Statistics and Machine Learning Toolbox Version 12.2 und die Wavelet Toolbox Version 6.0 verwendet.
MCA Microsoft 365 Certified Associate Modern Desktop Administrator Complete Study Guide with 900 Practice Test Questions: Exam MD-100 and Exam MD-101
by William PanekComplete, UPDATED study guide for MCA Modern Desktop Administrator certification exams, MD-100 and MD-101. Covers new Windows 11, services, technologies, and more! MCA Microsoft 365 Certified Associate Modern Desktop Administrator Complete Study Guide, Second Edition, is your all-in-one guide to preparing for the exams that will earn you the MCA Modern Desktop Administrator certification! In this book, well-known Windows guru and five-time Microsoft MVP, William Panek, guides you through the latest versions of the Windows Client exam (MD-100) and the Managing Modern Desktops exam (MD-101). This one-stop resource covers 100% of the objectives for both exams, providing real world scenarios, hands-on exercises, and challenging review questions. You’ll also dive deeper into some of the more complex topics and technologies, including deploying, maintaining, and upgrading Windows; managing devices and data; configuring storage and connectivity; managing apps and data; and more. Learn everything you need to know to pass the MD-100 and MD-101 exams Earn your MCA Modern Desktop Administrator certification to launch or advance your career Access exercises, review questions, flashcards, and practice exams, in the book and online Master all of the test objectives for the latest exam versions—updated for Windows 11With this study guide, you also get access to Sybex’s superior online learning environment, including an assessment test, hundreds of practice exams, flashcards, searchable glossary, and videos for many of the chapter exercises. This is the perfect test prep resource for admins preparing for certification and anyone looking to upgrade their existing skills to Microsoft’s latest desktop client.