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Brian Hahn, Daniel Valentine ... 424 pages - Publisher: Academic Press; 5th edition (January, 2013) ... Language: English - ISBN-10: 0123943981 - ISBN-13: 978-0123943989 ...

The fifth edition of Essential MATLAB for Engineers and Scientists provides a concise, balanced overview of MATLAB's functionality that facilitates independent learning, with coverage of both the fundamentals and applications. The essentials of MATLAB are illustrated throughout, featuring complete coverage of the software's windows and menus. Program design and algorithm development are presented clearly and intuitively, along with many examples from a wide range of familiar scientific and engineering areas. This is an ideal book for a first course on MATLAB or for an engineering problem-solving course using MATLAB, as well as a self-learning tutorial for professionals and students expected to learn and apply MATLAB. Updated with the features of MATLAB R2012b + Expanded discussion of writing functions and scripts + Revised and expanded Part II: Applications + Expanded section on GUIs + More exercises and examples throughout + Companion website for students providing M-files used within the book and selected solutions to end-of-chapter problems.

Machine Learning, Classification and Algorithms using MATLAB: Learn to Implement Classification Algorithms In One of the Most Power Tool used by Scientists and Engineer.

 This course is designed to cover one of the most interesting areas of machine learning called classification. I will take you step-by-step in this course and will first cover the basics of MATLAB. Following that we will look into the details of how to use different machine learning algorithms using MATLAB. Specifically, we will be looking at the MATLAB toolbox called statistic and machine learning toolbox. We will implement some of the most commonly used classification algorithms such as K-Nearest Neighbor, Naive Bayes, Discriminant Analysis, Decision Tress, Support Vector Machines, Error Correcting Output Codes and Ensembles. Following that we will be looking at how to cross validate these models and how to evaluate their performances. Intuition into the classification algorithms is also included so that a person with no mathematical background can still comprehend the essential ideas. The following are the course outlines. Segment 1: Grabbing and Importing Dataset + Segment 2: K-Nearest Neighbor + Segment 3: Naive Bayes + Segment 4: Decision Trees + Segment 5: Discriminant Analysis + Segment 6: Support Vector Machines + Segment 7: Error Correcting Output Codes + Segment 8: Classification with Ensembles + Segment 9: Validation Methods + Segment 10: Evaluating Performance.

Dan B. Marghitu, Mihai Dupac, Nels H. Madsen ... 286 pages - Publisher: Springer; (2013)... Language: English - ISBN-10: 1447151097 - ISBN-13: 978-1447151098 ...

Engineering mechanics involves the development of mathematical models of the physical world. Statics addresses the forces acting on and in mechanical objects and systems. Statics with MATLAB® develops an understanding of the mechanical behavior of complex engineering structures and components using MATLAB® to execute numerical calculations and to facilitate analytical calculations. MATLAB® is presented and introduced as a highly convenient tool to solve problems for theory and applications in statics. Included are example problems to demonstrate the MATLAB® syntax and to also introduce specific functions dealing with statics. These explanations are reinforced through figures generated with MATLAB® and the extra material available online which includes the special functions described. This detailed introduction and application of MATLAB® to the field of statics makes Statics with MATLAB® a useful tool for instruction as well as self study, highlighting the use of symbolic MATLAB® for both theory and applications to find analytical and numerical solutions. 

Aaron R. Bradley ... 238 pages -Publisher: Springer; (October, 2011) ... Language: English - ISBN-10: 3642233023 - ISBN-13: 978-3642233029

To learn to program is to be initiated into an entirely new way of thinking about engineering, mathematics, and the world in general. Computation is integral to all modern engineering disciplines, so the better you are at programming, the better you will be in your chosen field. The author departs radically from the typical presentation by teaching concepts and techniques in a rigorous manner rather than listing how to use libraries and functions. He presents pointers in the very first chapter as part of the development of a computational model that facilitates an ab initio presentation of subjects such as function calls, call-by-reference, arrays, the stack, and the heap. The model also allows students to practice the essential skill of memory manipulation throughout the entire course rather than just at the end. As a result, this textbook goes further than is typical for a one-semester course -- abstract data types and linked lists, for example, are covered in depth. The computational model will also serve students in their adventures with programming beyond the course: instead of falling back on rules, they can think through the model to decide how a new programming concept fits with what they already know. The book is appropriate for undergraduate students of engineering and computer science, and graduate students of other disciplines. It contains many exercises integrated into the main text, and the author has made the source code available online.

Stephen J. Chapman ... 592 pages - Publisher: CL Engineering; 4th edition (November, 2007) ... Language: English - ISBN-10: 049524449X - ISBN-13: 978-0495244493 ...

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.

David E. Hiebeler ... 233 pages - Publisher: Chapman and Hall/CRC; (June, 2015) ... Language: English - ISBN-10: 1466568380 - ISBN-13: 978-1466568389 ... 

The First Book to Explain How a User of R or MATLAB Can Benefit from the Other: In today’s increasingly interdisciplinary world, R and MATLAB® users from different backgrounds must often work together and share code. R and MATLAB® is designed for users who already know R or MATLAB and now need to learn the other platform. The book makes the transition from one platform to the other as quick and painless as possible. Enables R and MATLAB Users to Easily Collaborate and Share Code: The author covers essential tasks, such as working with matrices and vectors, writing functions and other programming concepts, graphics, numerical computing, and file input/output. He highlights important differences between the two platforms and explores common mistakes that are easy to make when transitioning from one platform to the other.

Stephen J. Chapman ... 432 pages - Publisher: CL Engineering; 2nd edition (November, 2008) ... Language: English - ISBN-10: 049529568X - ISBN-13: 978-0495295686 ...

Stephen Chapman's Essentials of MATLAB Programming is a successful freshman-level text that is useable in a wide range of courses. This brief text serves two purposes - it teaches how to program using MATLAB as a technical programming language as well as teaching students the basics of computer programming. Using top-down design methodology, the text encourages students to think about the proper design of a program before coding. Problem solving skills as well as the ability to locate desired functions within MATLAB are also presented making this text a useful reference tool.

Machine Learning Classification Algorithms using MatLab [Size: 580 MB] ... This course is designed to cover one of the most interesting areas of machine learning called classification. I will take you step-by-step in this course and will first cover the basics of MATLAB. Following that we will look into the details of how to use different machine learning algorithms using MATLAB. Specifically, we will be looking at the MATLAB toolbox called statistic and machine learning toolbox. We will implement some of the most commonly used classification algorithms such as K-Nearest Neighbor, Naive Bayes, Discriminant Analysis, Decision Tress, Support Vector Machines, Error Correcting Output Codes and Ensembles. Following that we will be looking at how to cross validate these models and how to evaluate their performances. Intuition into the classification algorithms is also included so that a person with no mathematical background can still comprehend the essential ideas. The following are the course outlines.

Table of Contents: - Segment 1: Instructor and Course Introduction - Segment 2: MATLAB Crash Course - Segment 3: Grabbing and Importing Dataset - Segment 4: K-Nearest Neighbor - Segment 5: Naive Bayes - Segment 6: Decision Trees - Segment 7: Discriminant Analysis - Segment 8: Support Vector Machines - Segment 9: Error Correcting Output Codes - Segment 10: Classification with Ensembles - Segment 11: Validation Methods - Segment 12: Evaluating Performance. This course is really good for a beginner. It will help you to start from the ground up and move on to more complicated areas. You receive knowledge from a Ph.D. in Computer science (machine learning) with over 10 years of teaching and research experience.

Learn Neural Networks using Matlab Course [Size: 187 MB] ... MATLAB (matrix laboratory) is a multi-paradigm numerical computing environment and fourth-generation programming language developed by MathWorks. Although MATLAB is intended primarily for numerical computing, but by optional toolboxes, using the MuPAD symbolic engine, has access to symbolic computing capabilities too. One of these toolboxes is Neural Network toolbox. This toolbox is free, open source software for simulating models of brain and central nervous system, based on MATLAB computational platform. In these courses you will learn the general principles of Neural Network Toolbox designed in Matlab and you will be able to use this Toolbox efficiently as well.

The list of contents is: - Introduction: in this chapter the Neural Network Toolbox is Defined and introduced. An overview of neural network application is provided and the neural network training process for pattern recognition, function fitting and clustering data in demonstrated. - Neuron models:  A description of the neuron model is provided, including simple neurons, transfer functions, and vector inputs and single and multiple layers neurons are explained. The format of input data structures is very effective in the simulation results of both static and dynamic networks. So this effect is discussed in this chapter too. And finally the incremental and batch training rule is explained. - Perceptron networks: In this chapter the perceptron architecture is shown and it is explained how to create a perceptron in Neural network toolbox. The perceptron learning rule and its training algorithm is discussed and finally the network/Data manager GUI is explained. - Linear filters: in this chapter linear networks and linear system design function is discussed. The tapped delay lines and linear filters are discussed and at the end of the chapter LMS algorithm and linear classification algorithm used for linear filters are explained. - Backpropagation networks: The architecture, simulation, and several high-performance backpropagation training algorithms of backpropagation networks are discussed in this chapter. - Conclusion: in this chapter the memory and speed of different backpropagation training algorithms are illustrated. And at the end of the chapter all these algorithms are compared to help you select the best training algorithm for your problem in hand. - Matlab Software Installation: You are required to install the Matlab Software on your machine, so you can start executing the codes, and examples we work during the course.

Amos Gilat, Vish Subramaniam ... 480 pages - Publisher: Wiley; 1st edition (April, 2007) ... Language: English - ISBN-10: 0471734403 - ISBN-13: 978-0471734406 ...

Following a unique approach, this innovative book integrates the learning of numerical methods with practicing computer programming and using software tools in applications. It covers the fundamentals while emphasizing the most essential methods throughout the pages. Readers are also given the opportunity to enhance their programming skills using MATLAB to implement algorithms. They'll discover how to use this tool to solve problems in science and engineering. A clear and concise guide to numerical methods and their application: Mastering numerical methods has never been easier than with Gilat/Subramaniam’s Numerical Methods For Engineers and Scientists: An Introduction with Applications Using MATLAB. Uniquely accessible and concise, this book takes an innovative approach that integrates the study of numerical methods with hands-on programming practice using the popular MATLAB environment to solve realistic problems in engineering and science. Ideal for both students and professionals who would like to become more adept at numerical methods, Numerical Methods For Engineers and Scientists familiarizes you with: The mathematical background and fundamentals of numerical methods + Solving  nonlinear equations + Solving a system of linear equations + Eigenvalues and Eigenvectors + Function approximation, curve fitting, and interpolation + Differentiation + Integration + First-order and higher-order ODEs + Initial and boundary value problems. Using MATLAB’s built-in functions as tools for solving problems, you will practice applying numerical methods for analysis of real-world problems. All the information is presented in manageable, step-by-step fashion, supported by a large number of annotated examples and end-of-chapter problems. Lucid, carefully structured, and flexibly designed to fulfill a wide range of academic and practical needs, this book will help you develop the skills in numerical methods that will serve you well as a practicing engineer.

Amos Gilat ... 416 pages - Publisher: Wiley; 5th edition (January, 2014) ... Language: English- ISBN-10: 1118629868 - ISBN-13: 978-1118629864 ...

More college students use Amos Gilat’s MATLAB: An Introduction with Applications than any other MATLAB textbook. This concise book is known for its just-in-time learning approach that gives students information when they need it. The new edition gradually presents the latest MATLAB functionality in detail. Equally effective as a freshmen-level text, self-study tool, or course reference, the book is generously illustrated through computer screen shots and step-by-step tutorials, with abundant and motivating applications to problems in mathematics, science, and engineering.

Eugeniy E. Mikhailov ... 266 pages - Publisher: CRC Press; 1st edition (February, 2018) ... Language: English - ISBN-10: 1498738281 - ISBN-13: 978-1498738286 ...

This book offers an introduction to the basics of MATLAB programming to scientists and engineers. The author leads with engaging examples to build a working knowledge, specifically geared to those with science and engineering backgrounds. The reader is empowered to model and simulate real systems, as well as present and analyze everyday data sets. In order to achieve those goals, the contents bypass excessive "under the hood" details, and instead gets right down to the essential, practical foundations for successful programming and modeling. Readers will benefit from the following features: Teaches programming to scientists and engineers using a problem-based approach, leading with illustrative and interesting examples. + Emphasizes a hands-on approach, with "must know" information and minimal technical details. + Utilizes examples from science and engineering to showcase the application of learned concepts on real problems. + Showcases modeling of real systems, gradually advancing from simpler to more challenging problems. + Highlights the practical uses of data processing and analysis in everyday life.

Won Y. Yang, Young K. Choi, Jaekwon Kim, Man Cheol Kim, H. Jin Kim, Taeho Im ... 755 pages - Publisher: Chapman and Hall/CRC; 1st edition (February, 2018) ... Language: English - ISBN-10: 1138059331 - ISBN-13: 978-1138059337 ...

The aim of this book is to help the readers understand the concepts, techniques, terminologies, and equations appearing in the existing books on engineering mathematics using MATLAB. Using MATLAB for computation would be otherwise time consuming, tedious and error-prone. The readers are recommended to have some basic knowledge of MATLAB.

Matthew P. Coleman ... 683 pages - Publisher: Chapman and Hall/CRC; 2nd edition (June, 2013) ... Language: English - ISBN-10: 1439898464 - ISBN-13: 978-1439898468 ...

An Introduction to Partial Differential Equations with MATLAB®, Second Edition illustrates the usefulness of PDEs through numerous applications and helps students appreciate the beauty of the underlying mathematics. Updated throughout, this second edition of a bestseller shows students how PDEs can model diverse problems, including the flow of heat, the propagation of sound waves, the spread of algae along the ocean’s surface, the fluctuation in the price of a stock option, and the quantum mechanical behavior of a hydrogen atom. Suitable for a two-semester introduction to PDEs and Fourier series for mathematics, physics, and engineering students, the text teaches the equations based on method of solution. It provides both physical and mathematical motivation as much as possible. The author treats problems in one spatial dimension before dealing with those in higher dimensions. He covers PDEs on bounded domains and then on unbounded domains, introducing students to Fourier series early on in the text.

Cesar Perez Lopez ... 368 pages - Publisher: Apress; 1st edition (December, 2014) ... Language: English - ISBN-10: 148420350X - ISBN-13: 978-1484203507 ...

MATLAB Mathematical Analysis is a reference book that presents the techniques of mathematical analysis through examples and exercises resolved with MATLAB software. The purpose is to give you examples of the mathematical analysis functions offered by MATLAB so that you can use them in your daily work regardless of the application. The book supposes proper training in the mathematics and so presents the basic knowledge required to be able to use MATLAB for calculational or symbolic solutions to your problems for a vast amount of MATLAB functions. The book begins by introducing the reader to the use of numbers, operators, variables and functions in the MATLAB environment. Then it delves into working with complex variables. A large section is devoted to working with and developing graphical representations of curves, surfaces and volumes. MATLAB functions allow working with two-dimensional and three-dimensional graphics, statistical graphs, curves and surfaces in explicit, implicit, parametric and polar coordinates. Additional work implements twisted curves, surfaces, meshes, contours, volumes and graphical interpolation. The following part covers limits, functions, continuity and numerical and power series. Then differentiation is addressed in one and several variables including differential theorems for vector fields. Thereafter the topic of integration is handled including improper integrals, definite and indefinite integration, integration in multiple variables and multiple integrals and their applications. Differential equations are exemplified in detail, Laplace transforms, Tayor series, and the Runga-Kutta method and partial differential equations.

Bassem R. Mahafza ... 552 pages - Publisher: Chapman and Hall/CRC; 1st edition (June, 2000) ... Language: English - ISBN-10: 1584881828 - ISBN-13: 978-1584881827 ...

Imagine the ideal radar book. What criteria define it?: Provides a detailed useful reference for working engineers and can serve as an advanced graduate textbook * Stands on its own as a complete presentation of the subject * Includes examples and exercise problems * Helps readers move beyond the theory into the real world of radar design and analysis. Radar Systems Analysis and Design Using MATLAB does all this and more. Based on the philosophy that radar systems should not be difficult to understand or complicated to analyze and design, it focuses on radar fundamentals, principles, and rigorous but easy-to-follow derivations. Each chapter provides all the necessary mathematical and analytical coverage needed for understanding radar theory. Among this book's most outstanding features is the integration of Matlab 5.0 functions and programs within each chapter to further enhance understanding of the theory and provide a source for establishing radar system design requirements. All of these functions and programs can be downloaded from the CRC Web site - saving users more than $1,000 in acquiring similar software. All of this plus nearly 1,300 equations, almost 300 illustrations, more than 200 examples and end-of-chapter problems, and six appendices means that Radar Systems Analysis and Design Using MATLAB meets all the criteria. Your search for the ideal resource for radar engineering is over.

Martin H. Trauth ... 427 pages ... Publisher: Springer; 4th edition (February, 2015) ... Language: English - AmazonSIN: B018C2STZU.

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.

H. Mendel ... 218 pages - Publisher: CreateSpace Independent Publ.; (October, 2016) ... Language: English - ISBN-10: 1539439321 - ISBN-13: 978-1539439325 ...

This book initiates the reader into the techniques of data analysis with MATLAB. The major contents are as follows: Data Processing Importing and Exporting Data Plotting Data Missing Data Representing Missing Data Values Working with NaNs Interpolating Missing Data Inconsistent Data Filtering Data Detrending Data Differencing Data Interactive Data Exploration Marking Up Graphs with Data Brushing Making Graphs Responsive with Data Linking Interacting with Graphed Data Data Brushing with the Variables Editor Using Data Tips to Explore Graphs Descriptive Statistics Functions for Calculating Descriptive Statistics Regression Analysis Linear Correlation Linear Regression Fitting Data with Curve Fitting Toolbox Functions Interactive Fitting Programmatic Fitting MATLAB Functions for Polynomial Models Linear Model with Nonpolynomial Terms Multiple Regression Time Series Analysis Time Series Objects Time Series Data Sample Time Series Constructor Time Series Tools Importing and Exporting Data Plotting Time Series Selecting Data for Analysis Editing Data, Time, Attributes, and Events Processing and Manipulating Time Series

GUIs (also known as graphical user interfaces or UIs) provide point-and-click control of software applications, eliminating the need to learn a language or type commands in order to run the application. MATLAB apps are self-contained MATLAB programs with GUI front ends that automate a task or calculation. The GUI typically contains controls such as menus, toolbars, buttons, and sliders. Many MATLAB products, such as Curve Fitting Toolbox, Signal Processing Toolbox, and Control System Toolbox include apps with custom user interfaces. You can also create your own custom apps, including their corresponding UIs, for others to use.

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