Mastering MATLAB 7 Review

Average Reviews:

(More customer reviews)Are you looking to buy Mastering MATLAB 7? Here is the right place to find the great deals. we can offer discounts of up to 90% on Mastering MATLAB 7. Check out the link below:

>> Click Here to See Compare Prices and Get the Best Offers

Mastering MATLAB 7 ReviewI have been using a copy of this reference since I got started with Matlab about a year and a half ago. It is very good for beginners who need to look up how to do general tasks such as write a function using variable arguments, perform plotting, or figure out how to shoe-horn a problem into Matlab that doesn't really seem to fit the Matlab paradigm of everything being a matrix. I also particularly like the chapter on using Matlab with Java. Of course, if you are a more advanced user, this book will seem too simplistic. Even now, though, it's the first book I go to when I have a question that does not involve one of the specialized Matlab toolboxes. The table of contents is not shown by Amazon, so I show it here for the purpose of completeness:
1 GETTING STARTED
Introduction; Typographical Conventions; What's New in MATLAB 7; What's in Mastering MATLAB 7
2 BASIC FEATURES
Simple Math; The MATLAB Workspace; About Variables; Comments, Punctuation, and Aborting Execution; Complex Numbers;Floating-Point Arithmetic;Mathematical Functions
3 THE MATLAB DESKTOP
MATLAB Windows; Managing the MATLAB Workspace; Memory Management; Number Display Formats; Keeping a Session Log;System Information; The MATLAB Search Path
4 SCRIPT M-FILES
Script M-file Use; Block Comments and Code Cells; Setting Execution Time; Startup and Finish
5 ARRAYS AND ARRAY OPERATIONS
Simple Arrays; Array Addressing or Indexing; Array Construction; Array Orientation; Scalar-Array Mathematics; Array-Array Mathematics; Standard Arrays; Array Manipulation; Array Sorting; Subarray Searching; Array Manipulation Functions; Array Size; Arrays and Memory Utilization
6 MULTIDIMENSIONAL ARRAYS
Array Construction; Array Mathematics and Manipulation; Array Size
7 NUMERIC DATA TYPES
Integer Data Types; Floating Point Data Types; Summary
8 CELL ARRAYS AND STRUCTURES
Cell Array Creation; Cell Array Manipulation; Retrieving Cell Array Content; Comma-Separated Lists; Cell Functions; Cell Arrays of Strings; Structure Creation; Structure Manipulation; Retrieving Structure Content; Comma-Separated Lists (Again); Structure Functions; Summary
9 CHARACTER STRINGS
String Construction; Numbers to Strings to Numbers; String Evaluation; String Functions; Cell Arrays of Strings; Searching Using Regular Expressions
10 RELATIONAL AND LOGICAL OPERATIONS
Relational Operators; Logical Operators; Operator Precedence; Relational and Logical Functions; NaNs and Empty Arrays
11 CONTROL FLOW
For Loops; While Loops; If-Else-End Constructions; Switch-Case Constructions; Try-Catch Blocks
12 FUNCTIONS
M-file Function Construction Rules; Input and Output Arguments; Function Workspaces; Functions and the MATLAB Search Path; Creating Your Own Toolbox; Command-Function Duality; Function Handles and Anonymous Functions; Nested Functions;
13 M-FILE DEBUGGING AND PROFILING
Debugging Tools; Syntax Checking and File Dependencies; Profiling M-files
14 FILE AND DIRECTORY MANAGEMENT
Native Data Files; Data Import and Export; Low-Level File I/O; Directory Management; FTP File Operations
15 SET, BIT, AND BASE FUNCTIONS
Set Functions; Bit Functions; Base Conversions
16 TIME COMPUTATIONS
Current Date and Time; Date Format Conversions; Date Functions; Timing Functions; Plot Labels
17 MATRIX ALGEBRA
Sets of Linear Equations; Matrix Functions; Special Matrices; Sparse Matrices; Sparse Matrix Functions
18 DATA ANALYSIS
Basic Statistical Analysis; Basic Data Analysis; Data Analysis and Statistical Functions
19 DATA INTERPOLATION
One-Dimensional Interpolation; Two-Dimensional Interpolation; Triangulation and Scattered Data; Summary
20 POLYNOMIALS
Roots; Multiplication; Addition; Division; Derivatives and Integrals; Evaluation; Rational Polynomials; Curve Fitting
21 CUBIC SPLINES
Basic Features; Piecewise Polynomials; Cubic Hermite Polynomials; Integration; Differentiation; Spline Interpolation on a Plane
22 FOURIER ANALYSIS
Discrete Fourier Transform; Fourier Series
23 OPTIMIZATION
Zero Finding; Minimization in One Dimension; Minimization in Higher Dimensions; Practical Issues
24 INTEGRATION AND DIFFERENTIATION
Integration; Differentiation
25 DIFFERENTIAL EQUATIONS
IVP Format; ODE Suite Solvers; Basic Use; Setting Options; BVPs, PDEs and DDEs
26 TWO-DIMENSIONAL GRAPHICS
The plot Function; Linestyles, Markers, and Colors; Plot Grids, Axes Box, and Labels; Customizing Plot Axes; Multiple Plots; Multiple Figures; Subplots Interactive Plotting Tools; Screen Updates; Specialized 2-D Plots; Easy Plotting; Text Formatting; Summary
27 THREE-DIMENSIONAL GRAPHICS
Line Plots; Scalar Functions of Two Variables; Mesh Plots; Surface Plots; Mesh and Surface Plots of Irregular Data; Changing Viewpoints; Camera Control; Contour Plots; Specialized 3-D Plots; Volume Visualization; Easy Plotting; Summary
28 USING COLOR AND LIGHT
Understanding Colormaps; Using Colormaps; Displaying Colormaps; Creating and Altering Colormaps; Using Color to Describe a Fourth Dimension; Lighting Models; Summary
29 IMAGES, MOVIES, AND SOUND
Images; Image Formats; Image Files; Movies; Image Utilities; Sound; Summary
30 PRINTING AND EXPORTING GRAPHICS
Printing and Exporting Using Menus; Command Line Printing and Exporting; Printers and Export File Formats; PostScript Support; Choosing a Renderer; Handle Graphics Properties; Setting Defaults; Summary
31 HANDLE GRAPHICS
Objects; Object Handles;Object Properties; get and set; Finding Objects; Selecting Objects with the Mouse; Position and Units; Default Properties; Common Properties Plot Objects Group Objects; Annotation Axes; Linking Objects; New Plots; Rendering Speed; Callbacks; M-file Examples; Summary
32 GRAPHICAL USER INTERFACES
What's a GUI?; Predefined Dialog Boxes; M-file Dialog Boxes; Dialog Box Summary; GUI Object Hierarchy; GUI Creation Fundamentals; GUI Object Size and Position; Capturing Mouse Actions; The Event Queue; Callback Programming M-file Examples; GUIDE; Summary
33 MATLAB CLASSES AND OBJECT-ORIENTED PROGRAMMING
Overloading; Class Creation; Subscripts; Converter Functions; Precedence, Inheritance, and Aggregation
34 MATLAB PROGRAMMING INTERFACES
Accessing MATLAB Arrays; Calling C or FORTRAN from MATLAB; Calling MATLAB from C or FORTRAN; Exchanging Data with MAT-files; Shared Libraries; Serial Communications; Source Code Control Systems; Summary
35 EXTENDING MATLAB WITH JAVA
Java Overview; Java Classes; Java Objects; Java Methods; Object Properties; Data Exchange; Java Arrays; Java Functions; Examples; Summary
36 WINDOWS APPLICATION INTEGRATION
COM Objects: Client/Server Communication; Dynamic Data Exchange; MATLAB Notebook; MATLAB COM-related Toolboxes; Summary
37 GETTING HELP
Command Window Help; The Help Browser; Internet Resources; Mastering MATLAB 7 Help; Summary
38 EXAMPLES, EXAMPLES, EXAMPLES
Vectorization; JIT-Acceleration; Up-Down Sequence; Vandermonde Matrix; Repeated Value Creation and Counting; Differential Sums; Structure Manipulation; Inverse Interpolation; Polynomial Fitting; Nonlinear Curve Fitting; Picture-in-a-Picture Zoom
Mastering MATLAB 7 Overview This book covers all essential aspects of MATLAB presented within an easy-to-follow "learn while doing" tutorial format. Discussees all new features of the latest release of MATLAB. Discusses integration of MATLAB with C, FORTRAN, AND Java; increases MATLAB's power and flexibility in dealing with external algorithms, datasets, and operating system capabilities. Offers thorough coverage of indexing, vectorizing, and linear algebra. Features abundant examples throughout and includes a chapter that specifically covers extensive examples. Includes a comprehensive index. A useful reference for engineers or anyone who uses MATLAB.

Want to learn more information about Mastering MATLAB 7?

>> Click Here to See All Customer Reviews & Ratings Now

Read More...

Numerical Methods Using Matlab (4th Edition) Review

Average Reviews:

(More customer reviews)Are you looking to buy Numerical Methods Using Matlab (4th Edition)? Here is the right place to find the great deals. we can offer discounts of up to 90% on Numerical Methods Using Matlab (4th Edition). Check out the link below:

>> Click Here to See Compare Prices and Get the Best Offers

Numerical Methods Using Matlab (4th Edition) ReviewWhether you are an instructor for an Engineering class, Life Sciences, Statistics, Mathematics, or simply want to add practical mathematical analysis and programming, this book is the book you should use. I have been using Matlab for a number of years, and I had to pick up my Matlab knowledge from the manuals, man pages, the Internet, etc... and finding out the ins and outs of how to do something was not always an easy task nor accurate. Mathews and Fink's book put all you need to know about the most popular Mathematical methods at your finger tips. The book is tailored such that it can be used alone in a Mathematics course, or as reference in an Engineering course. One field of study that has enjoyed the power and flexibility of Matlab in the recent years is Computational Biology or Bioinformatics. Even though there are plenty of applications popping up here and there for this area of research, the area is still very much untapped and algorithms need to be developed for it as we go forward. Matlab is the best way to try out these new or improved algorithms, and use some of the available tools out there to generate C source code from your Matlab files. This method of algorithms development could save you tons of time, since Matlab makes numerical programming very simple.
The authors start with the basics in Numerical Methods; assuming that this book will be used as the primary text book in the course. A very good assumption, and the instructors who choose otherwise, can always skip the preliminaries. The context of text aims to provide a good balance of theory and application. One way that the authors try to keep this balance is to talk about "error" rate for the algorithms in question. The students are thought the limitations of Matlab along with the strengths of the software, and error analysis is one way to show the students that the results of numerical analysis is Matlab is not perfect, and more importantly why. This error analysis is done for every major algorithm and method presented in the text, and a number of methodologies are presented to help the student in figuring out this rate.
Authors start the main contents of the book with a representation of basic Linear Systems followed by a more complicated topic of Polynomial Approximation. Taylor Series and Lagrange Approximations are thoroughly covered in theory followed by examples that are solved by "hand" and by Matlab. The examples are complete, and can even be used, at least to start with, for the problem sets at the end of the chapter. As one would guess, curve fitting is the next topic of discussion. As you know, numerical techniques in science and engineering often requires curve fitting of experimental data. Starting with simple techniques of Least-Squares Lines, non-Linear Least-Square Methods and ending with the four different flavors of Spline Functions. The Matlab examples becomes more advanced as the topic progresses, and more and more examples are given as the topics get more complicated as well.
One can not learn Numerical Methods without a deep understanding of Numerical Differentiation and Numerical Integrations. Numerical methods for Differentiation are used to solve boundary value problems in ordinary differential equations and partial differential equations. Heat Transfer, Semiconductor Physics and Device Modeling, an Physical modeling of Molecules are just some of the examples that use these numerical differentiation techniques to solve problems. As is the case with the book, the authors start talking the theory behind how numerical differentiation works, and then, they go into the Matlab representation of the problem. Various approximation methods are presented, and error rate for each approximation method is also calculated in detail - both by hand and using Matlab.
Numerical Integration is a bit more difficult, as there are a number of ways to calculate the area under a curve. The authors present four numerical methods in detail: quadrature, composite trapezoidal, adaptive quadrature and Gauss-Legendre Integration. Each theory is followed by an example Matlab programs. The authors wrap up the text by talking about differential equations and partials differential equations. These two topics are difficult without using numerical methods, and it is even harder to follow the numerical theory of these topics. The authors take a slightly different approach to these topics. They start with examples from the get go. Instead of laying down the theory, they start each chapter with relevant examples from simple to more complex and abstract. Wave Equations and Heat Transfer equations are well known applications of PDE that are presented in detail. Eigenvalues, eigenvectors and the Jacodi's Meothod wrap up this text by j. H. Mathews and K. D. Fink.
I would recommend this book to be used for second year Mathematics, Physical Sciences or Engineering students. A course in Numerical Methods would benefit greatly from this book. Other students can certainly use this text to assist them with modeling, simulation and statistical problems in Electrical Engineering, Mechanical Engineering and various Applied Chemistry and Physics courses.
Numerical Methods Using Matlab (4th Edition) Overview This book provides a fundamental introduction to numerical analysis.This book covers numerous topics including Interpolation and Polynomial Approximation,Curve Fitting, Numerical Differentiation, Numerical Integration, and Numerical Optimization. For engineering and computer science fields.

Want to learn more information about Numerical Methods Using Matlab (4th Edition)?

>> Click Here to See All Customer Reviews & Ratings Now

Read More...

Computational Intelligence Paradigms: Theory & Applications using MATLAB Review

Average Reviews:

(More customer reviews)Are you looking to buy Computational Intelligence Paradigms: Theory & Applications using MATLAB? Here is the right place to find the great deals. we can offer discounts of up to 90% on Computational Intelligence Paradigms: Theory & Applications using MATLAB. Check out the link below:

>> Click Here to See Compare Prices and Get the Best Offers

Computational Intelligence Paradigms: Theory & Applications using MATLAB ReviewWhile this book's technical content (e.g. neural net discussion) is quite good, I can't believe that the editor allowed such poor language to pass through the editing process. This book is probably the best example of the kind of linguistic degradation that George Orwell mentioned in "Politics and the English Language." Virtually every sentence contains pseudo-sophisticated words that appear to have been picked at random from a thesaurus. Synonyms usually convey a meaning similar, but not identical to, the original, but the authors never grasped this basic observation. Also, the authors seem not to understand the context in which a given word usually appears, thereby making pretty comical errors that distract the reader. Staying focused on the technical content while processing the linguistic gibberish is quite a challenge.Computational Intelligence Paradigms: Theory & Applications using MATLAB OverviewOffering a wide range of programming examples implemented in MATLAB, Computational Intelligence Paradigms: Theory and Applications Using MATLAB presents theoretical concepts and a general framework for computational intelligence (CI) approaches, including artificial neural networks, fuzzy systems, evolutionary computation, genetic algorithms and programming, and swarm intelligence. It covers numerous intelligent computing methodologies and algorithms used in CI research. The book first focuses on neural networks, including common artificial neural networks; neural networks based on data classification, data association, and data conceptualization; and real-world applications of neural networks. It then discusses fuzzy sets, fuzzy rules, applications of fuzzy systems, and different types of fused neuro-fuzzy systems, before providing MATLAB illustrations of ANFIS, classification and regression trees, fuzzy c-means clustering algorithms, fuzzy ART map, and Takagi-Sugeno inference systems. The authors also describe the history, advantages, and disadvantages of evolutionary computation and include solved MATLAB programs to illustrate the implementation of evolutionary computation in various problems. After exploring the operators and parameters of genetic algorithms, they cover the steps and MATLAB routines of genetic programming. The final chapter introduces swarm intelligence and its applications, particle swarm optimization, and ant colony optimization.Full of worked examples and end-of-chapter questions, this comprehensive book explains how to use MATLAB to implement CI techniques for the solution of biological problems. It will help readers with their work on evolution dynamics, self-organization, natural and artificial morphogenesis, emergent collective behaviors, swarm intelligence, evolutionary strategies, genetic programming, and the evolution of social behaviors.

Want to learn more information about Computational Intelligence Paradigms: Theory & Applications using MATLAB?

>> Click Here to See All Customer Reviews & Ratings Now

Read More...

A Guide to MATLAB Object-Oriented Programming Review

Average Reviews:

(More customer reviews)Are you looking to buy A Guide to MATLAB Object-Oriented Programming? Here is the right place to find the great deals. we can offer discounts of up to 90% on A Guide to MATLAB Object-Oriented Programming. Check out the link below:

>> Click Here to See Compare Prices and Get the Best Offers

A Guide to MATLAB Object-Oriented Programming ReviewI agree with Dimitri. This book was published in 2007, but was written for Matlab 5 to 7.1. Matlab is now on 7.6 and uses a classdef .m file to create a class.
I had created some of my own classes from the Matlab help using classdef command and so was completely confused when I first started looking at the code in this book because it doesn't use classdef. Now I understand my confusion, the book is way out of date.A Guide to MATLAB Object-Oriented Programming OverviewA Guide to MATLAB Object-Oriented Programming is the first book to deliver broad coverage of the documented and undocumented object-oriented features of MATLAB. Unlike the typical approach of other resources, this guide explains why each feature is important, demonstrates how each feature is used, and promotes an understanding of the interactions between features.
Assuming an intermediate level of MATLAB programming knowledge, the book not only concentrates on MATLAB coding techniques but also discusses topics critical to general software development. It introduces fundamentals first before integrating these concepts into example applications. In the first section, the book discusses eight basic functions: constructor, subsref, subsasgn, display, struct, fieldnames, get, and set. Building on the previous section, it explores inheritance topics and presents the Class Wizard, a powerful MATLAB class generation tool. The final section delves into advanced strategies, including containers, static variables, and function fronts.
With more than 20 years of experience designing and implementing object-oriented software, the expert author has developed an accessible and comprehensive book that aids readers in creating effective object-oriented software using MATLAB.

Want to learn more information about A Guide to MATLAB Object-Oriented Programming?

>> Click Here to See All Customer Reviews & Ratings Now

Read More...