Training - Courses

Objectives:

• Obtain a quick overview of The MathWorks and MATLAB
• Discuss course set-up, materials, and logistics
• Provide a “big picture” view of the course ahead

Objective: This section introduces the main features of the MATLAB integrated design environment and its user interfaces. Many themes for the course are established in this section, to be explored in detail in later sections.

• Interactively read data
• Interactively plot data
• Use expressions to compute new variables
• Generate a script to reproduce graphics with new data
• Export graphics for use in other applications

Objective: This section introduces MATLAB variables as data containers. Two essential operations are emphasized: creating variables and accessing the data the variables contain. The section also introduces MATLAB operations for computing with data.

• Creating variables
• Data import from external sources
• Data entry from the command line
• Matrix creation functions
• Accessing vector and matrix data (indexing)
• Row-column indexing
• Linear indexing
• Logical indexing
• Vector and matrix arithmetic
• Matrix and array operations
• Solving systems of linear equations
• Mathematical and statistical operations

Objective: This section introduces the visual side of MATLAB by showing you how to create plots of both vector and matrix data. Visualizations complement the numerical capabilities of MATLAB, and should play an equal role in any thorough data analysis.

• Vector Data
• Plane and space curves
• Annotating graphics
• Working with axes
• Data interpolation
• Plot types
• Matrix Data
• Images, contours, and surfaces
• Multidimensional data interpolation
• Volume visualization
• Plot types

Objective: M-files are the setting for MATLAB programming. This section gives an overview of how to write, edit, run, debug, and publish M-files. The distinction between script and function M-files is highlighted, and basic programming structures and best practices are introduced.

• The MATLAB Editor
• Script M-files
• The MATLAB path
• Cells and cell mode
• Publishing M-files
• Function M-files
• Subfunctions and nested functions
• Debugging
• Best practices
• Solution and analysis

Objective: This section highlights the data processing capabilities of MATLAB by looking at a few of the most common tools used in statistical analysis. MATLAB and the Statistics Toolbox have an extensive library of statistical functions and visualization methods that go well beyond the topics covered in this section. The goal of this section is to become familiar with the basic set-up for carrying out common statistical tasks.

• Data in MATLAB
• Descriptive statistics
• Covariance and correlation
• Convolution and smoothing
• Linear regression models
• Nonlinear regression models
• Discrete Fourier transform
• Spectral analysis with the fast Fourier transform (FFT)

Objective: This section provides an overview of the different types of variables (data containers) you can create in MATLAB. Data types differ from one another in the kind of data they may contain and the way the data is organized. The section focuses on two basic operations associated with any data type: how to construct a new variable of that type and, once it is constructed, how to access and use the data it contains. The section also discusses methods for converting among data types.

• What is a data type?
• Data types in MATLAB
• Methods for constructing and accessing types
• Nondouble arithmetic
• Converting types

Objective: Before you can do any kind of data analysis in MATLAB, you have to be able to import your data into the MATLAB environment. Likewise, when you have completed your analyses, you may want to export the results for purposes of recording and reporting. This section focuses on techniques for moving data back and forth between external files and data containers (variables) in the MATLAB workspace.

• File types and formats
• The Import Wizard
• Programmatic I/O
• Graphical I/O
• Low-level I/O
• Large files and irregular formats
• Real-time I/O

Objective: MATLAB is a language. You speak the language through programs. Whether you type in a single line of code at the command prompt or assemble multiple M-files into a sophisticated application, you are programming in the M language. This section reviews basic programming techniques and best practices, and then introduces some of the more advanced programming techniques that you can use to make your MATLAB programs robust, efficient, and user-friendly.

• Keywords and constructions
• Program structure
• Handling user input
• Improving code performance
• Function handles
• Graphics programming

Objective: This section shows you how to put a “friendly face” on your MATLAB pro¬grams in the form of a graphical user interface (GUI). GUIs allow users to interact with your programs without having to understand, or even see, the code that does the work in the background. GUIs also allow you to focus user attention on specific input/output behaviors of a program, while deemphasizing the intermediate mechanisms. GUIs offer many usability advantages over simple M-file programs.

• What is a GUI?
• Handle Graphics
• GUI design
• Using GUIDE
• Writing callbacks
• Modifying GUIs