Matlab (Version 9.3, R2017b, & Version 9.2, R2017a, & Version 9.1, R2016b, & Version 9.0, R2016a, & Version 8.6, R2015b, & Version 8.5, R2015a, & Version 8.1, R2013a, & Version 7.14, R2012a, & Version 7.11, R2010b, & 7.10, R2010a, & 7.7, R2008b, & 6.5, R13)
Documentation What is MATLAB? The MATLAB System About SIMULINK Available MATLAB Toolboxes |
Documentation
Matlab 9 (R2017b, R2017a, R2016b, R2016a) & 8 (R2015b, R2015a, R2013a)
You can reach the documentation of Matlab 8 (i.e. the Matlab Help Desk) within the Help botton at your Matlab window, or, if you are at the MATLAB prompt use the doc command, i.e.
>> doc
Note: Since release R2013b matlab needs CentOS 6 or newer. Release R2013a is the last release to run with CentOS 5!
Further information:
- Matlab Help Desk (WWW Online documentation)
- The Mathworks Home
- The Mathworks Home (Europe)
Matlab 7 (R2012a, R2010b, R2010a & R2008b)
You can reach the documentation of Matlab 7 (i.e. the Matlab Help Desk) within the Help botton at your Matlab window, or, if you are at the MATLAB prompt use the helpdesk command, i.e.
>> helpdesk
Note: Release 2012a was the last release of the 32-bit version of MATLAB for Linux. See the platform road map for more information.
Matlab 6.5 (R13)
One can reach the (local) online documentation of Matlab 6.5 (i.e. the Matlab Help Desk) within any web browser (locally from your LinuX box) via the link file:///net/appls/matlab6p5/help/helpdesk.html
. Or, if you are at the MATLAB prompt use the helpdesk command, i.e.
>> helpdesk
All manuals are available in HTML and PDF form.
If you are new to MATLAB and want to learn it fast, see the Getting Started manual for tutorials on the fundamentals of MATLAB.
Graphics is a collection of topics that explore all aspects of graphing with MATLAB, including plots, presentation graphics, and advanced visualization.
The online MATLAB Function Reference provides descriptions of all the MATLAB functions and operators. To find the information for a function, use either the listing by category or alphbetically. In addition, the Help Desk provides quick access to the descriptions of the Handle Graphics^{®} properties through the Handle Graphics Objects browser.
The External Interfaces/API introduces the external interfaces that are available with MATLAB. It also contains numerous C and Fortran examples that highlight this functionality.
Further information:
- Matlab 6.5 Help Desk: (Local Online documentation)
Note: Matlab 6.5 (R13) is available at all CentOS 4 LinuX computers via the command matlab6
.
Hint for handling PDF files within web browsers:
If you want to run acroread, xpdf or gv automatically from netscape or mosaic (and probably other browsers) when you click on a link to a PDF file, you need to edit (or create) the files .mime.types and .mailcap in your home directory. In .mime.types add the lines:
type=application/pdf
desc="Portable Document Format"
exts="pdf"
In .mailcap add the lines:
# Use Acrobat Reader to view PDF files.
application/pdf; acroread -tempFile %s
or
# Use xpdf to view PDF files.
application/pdf; xpdf -err %s
or
# Use gv to view PDF files.
application/pdf; gv %s
What is MATLAB?
MATLAB is a high-performance language for technical computing. It integrates computation, visualization, and programming in an easy-to-use environment where problems and solutions are expressed in an familiar mathematical notation. Typical uses include:
- Math and computation
- Algorithm development
- Modeling, simulation, and prototyping
- Data analysis, exploration, and visualization
- Scientific and engineering graphics
- Application development, including Graphical User Interface building
MATLAB is an interactive system whose basic data element is an array that does not require dimensioning. This allows you to solve many technical computing problems, especially those with matrix and vector formulations, in a fraction of the time it would take to write a program in a scalar noninteractive language such as C or Fortran.
The name MATLAB stands for matrix laboratory. MATLAB was originally written to provide easy access to matrix software developed by the LINPACK and EISPACK projects, which together represent the state-of-the-art in software for matrix computation.
MATLAB has evolved over a period of years with input from many users. In university environments, it is the standard instructional tool for introductory and advanced courses in mathematics, engineering, and science. In industry, MATLAB is the tool of choice for high-productivity research, development, and analysis.
MATLAB features a family of application-specific solutions called toolboxes. Very important to most users of MATLAB, toolboxes allow you to learn and apply specialized technology. Toolboxes are comprehensive collections of MATLAB functions (M-files) that extend the MATLAB environment to solve particular classes of problems. Areas in which toolboxes are available include signal processing, control systems, neural networks, fuzzy logic, wavelets, simulation, and many others.
The MATLAB System
The MATLAB system consists of five main parts:
The MATLAB language. This is a high-level matrix/array language with control flow statements, functions, data structures, input/output, and object-oriented programming features. It allows both "programming in the small" to rapidly create quick and dirty throw-away programs, and "programming in the large" to create complete large and complex application programs.
The MATLAB working environment. This is the set of tools and facilities that you work with as the MATLAB user or programmer. It includes facilities for managing the variables in your workspace and importing and exporting data. It also includes tools for developing, managing, debugging, and profiling M-files, MATLAB's applications.
Handle Graphics. This is the MATLAB graphics system. It includes high-level commands for 2-D and 3-D data visualization, image processing, animation, and presentation graphics. It also includes low-level commands that allow you to fully customize the appearance of graphics as well as to build complete Graphical User Interfaces on your MATLAB applications.
The MATLAB mathematical function library. This is a vast collection of computational algorithms ranging from elementary functions like sum, sine, cosine, and complex arithmetic, to more sophisticated functions like matrix inverse, matrix eigenvalues, Bessel functions, and fast Fourier transforms.
The MATLAB Application Program Interface (API). This is a library that allows you to write C and Fortran programs that interact with MATLAB. It include facilities for calling routines from MATLAB (dynamic linking), calling MATLAB as a computational engine, and for reading and writing MAT-files.
About SIMULINK
SIMULINK, a companion program to MATLAB, is an interactive system for simulating nonlinear dynamic systems. It is a graphical mouse-driven program that allows you to model a system by drawing a block diagram on the screen and manipulating it dynamically. It can work with linear, nonlinear, continuous-time, discrete-time, multivariable, and multirate system.
Blocksets are add-ins to SIMULINK that provide additional libraries of block for specialized applications like communications, signal processing, and power systems.
Real-time Workshop is a program that allows you to generate C code from your block diagrams and to run it on a variety of real-time systems.
For more information on SIMULINK see the tutorial and reference manual Roadmap SIMULINK.
Available MATLAB Toolboxes
Here is a list of professional toolboxes currently available on this site:
Control Systems
The Control System Toolbox, the foundation of the MATLAB control design toolbox family, contains functions for modeling, analyzing, and designing automatic control systems. The application of automatic control grows each year as sensors and computers become less expensive. As a result, automatic controllers are used not only in highly technical settings for automotive and aerospace systems, computer peripherals, and process control, but also in less obvious applications such as washing machines and cameras. See the Control System Toolbox.
Fuzzy Logic
The Fuzzy Logic Toolbox provides a complete set of GUI-based tools for designing, simulating, and analyzing fuzzy inference systems. Fuzzy logic provides an easily understandable, yet powerful way to map an input space to an output space with arbitrary complexity, with rules and relationships specified in natural language. Systems can be simulated in MATLAB or incorporated into a SIMULINK block diagram, with the ability to generate code for stand-alone execution. See the Fuzzy Logic Toolbox.
Image Processing
The Image Processing Toolbox contains tools for image processing and algorithm development. It includes tools for filter design and image restoration; image enhancement; analysis and statistics; color, geometric, and morphological operations; and 2-D transforms. See the Image Processing Toolbox.
MATLAB Compiler
The MATLAB Compiler takes M-files as input and generates C or C++ source code as output. The MATLAB Compiler can generate these kinds of source code:
- C source code for building MEX-files.
- C or C++ source code for combining with other modules to form stand-alone applications. Stand-alone applications do not require MATLAB at runtime; they can run even if MATLAB is not installed on the system. The MATLAB Compiler does require the MATLAB C/C++ Math Library to create stand-alone applications that rely on the core math and data analysis capabilities of MATLAB. The MATLAB Compiler also requires the MATLAB C/C++ Graphics Library in order to create stand-alone applications that make use of Handle Graphics^{®} functions.
- C code S-functions for use with Simulink^{®}.
- C shared libraries (dynamically linked libraries, or DLLs, on Microsoft Windows NT) and C++ static libraries. These can be used without MATLAB on the system, but they do require the MATLAB C/C++ Math Library.
See the Roadmanp MATLAB Compiler version 3.0.
Neural Networks
The Neural Network Toolbox by Howard Demuthand Mark Beale is a collection of MATLAB functions for designing and simulating neural networks. Neural networks are computing architectures, inspired by biological nervous systems, that are useful in applications where formal analysis is extremely difficult or impossible, such as pattern recognition and nonlinear system identification and control. See the Neural Networks Toolbox.
Optimization
The Optimization Toolbox contains commands for the optimization of general linear and nonlinear functions, including those with constraints. An optimization problem can be visualized as trying to find the lowest (or highest) point in a complex, highly contoured landscape. An optimization algorithm can thus be likened to an explorer wandering through valleys and across plains in search of the topographical extremes. See the Optimization Toolbox.
Partial Differential Equations (PDE)
Partial Differential Equations (PDE) Toolbox provides a powerfull and flexible environment for the study and solution of partial differential equations in two space dimensions and time. The equations are discretized by the Finite Element Method (FEM). the objectives of the PDE Tolbox are to provide you tools that:
- Define a PDE problem, i.e., define 2-D regions, boundary conditions, and PDE coefficients.
- Numerically solve the PDE problem, i.e., generate unstructured meshes, discretize the equations, and produce an approximation to the solution.
- Visualize the results.
The PDE Tolbox is designed for both beginners and advanced users.
The minimal requirement is that you can formulate a PDE problem on paper (draw the domain, write the boundary conditions, and the PDE). Start MATLAB. At the MATLAB comandline type:
>> pdetool
This invokes the graphical user interface (GUI), which is a self-contained graphical environment for PDE solving. For common applications you can use the specific physical terms rather than abstract coefficients. Using pdetool requires no knowledge of mathematics behind PDE, the numerical schemes, or MATLAB.
For more information on PDE, see the Partial Differential Equations Toolbox.
Signal Processing
The Signal Processing Toolbox contains tools for signal processing. Applications include audio (e.g., compact disc and digital audio tape), video (digital HDTV, image processing, and compression), telecommunications (fax and voice telephone), medicine (CAT scan, magnetic resonance imaging), geophysics, and econometrics. See the Signal Processing Toolbox.
Splines
The Spline Toolbox by Carl de Boor, a pioneer in the field of splines, provides a set of M-files for constructing and using splines, which are piecewise polynomial approximations. Splines are useful because they can approximate other functions without the unwelcome side effects that result from other kinds of approximations, such as piecewise linear curves. See the Spline Toolbox.
Statistics
The Statistics Toolbox provides a set of M-files for statistical data analysis, modeling, and Monte Carlo simulation, with GUI-based tools for exploring fundamental concepts in statistics and probability. See the Statistics Toolbox.
System Identification
The System Identification Toolbox, written by Lennart Ljung, is a collection of tools for estimation and identification. System identification is a way to find a mathematical model for a physical system (like an electric motor, or even a financial market) based only on a record of the system's inputs and outputs. See the System Identification Toolbox.
Wavelets
The Wavelet Toolbox extends the MATLAB Technical Computing Environment and provides a comprehensive collection of routines for examining local, multiscale, or nonstationary phenomena. Wavelet methods offer additional insight and performance in any application where Fourier techniques have been used. The toolbox is useful in many signal and image processing applications, including speech and audio processing, communications, geophysics, finance, and medicine.
The Wavelet Toolbox is a collection of functions built on the MATLAB Technical Computing Environment. It provides tools for the analysis and synthesis of signals and images using wavelets and wavelet packets within the framework of MATLAB.
The toolbox provides two categories of tools:
- Command line functions
- Graphical interactive tools
The first category of tools is made up of functions that you can call directly from the command line or from your own applications. Most os these functions are M-files, series of statements that implement specialized wavelet analysis or synthesis algorithms. You can view the code for these functions using the following statement:
>> type funtion_name
You can view thr header of the function, the help part, using the statement:
>> help funtion_name
A summary list of the Wavelet Toolbox functions is available to you by typing
>> help wavelet
You can change the way any toolbox function works by copying and renaming the M-file, then modifying your copy. You can also extent the toolbox by adding your own M-files.
The second category of tools is a collection of graphical interface tools that afford to extensive functionality. Access these tools by typing
>> wavemenu
from the command line.
Access more information on wavelets or wavelet toolbox demos by using the following statements:
>> waveinfo
>> wavedemo
or read the Wavelet Toolbox.