Mathtools.net Digest

February 2006
In this issue:
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Order a Free Informational CD:

Discover a New Way to Design Control Systems

View our Recorded Webinars

Video Processing System Design with MATLAB and Simulink

Mass Spectrometry Data Pre-Processing and Analysis Using MATLAB

Using Simulink Parameter Estimation and Test Data to Calibrate a Model of an Electric Motor

  Free Webinar: Introduction to MATLABŪ 7
This webinar, to be broadcast on March 2, introduces the MATLABŪ 7 product family and provides a high-level overview of the major capabilities. Through product demonstrations, attendees will see how the MATLAB 7 product family is used for programming and algorithm development, data acquisition and analysis, and application development and deployment.

http://www.mathworks.com/programs/mathtools/feb06/ml7/index.html

Swiftchart: Chart and Graph Java Applications
Swiftchart generates dynamic charts and graphs within JSP including bar, line, pie, stacked and grouped charts in both 2D and 3D. Features include antialiasing, multiple language support, cross-browser compatibility, Java Script parameter control, data labels, contextual data drill-down, CSV data sources, and more.

http://www.swiftchart.com/
http://www.mathtools.net/Java/Graphics_and_Visualization/

NewCode Memory Tuning System (MTS)
 MTS is up to five times faster than the GNU GPL Memory management. It is only one component of a system's dynamic performance, however, it can quickly become the dominant one. While a typical program spends no more than 40% of its runtime in functions related to memory management, an SMP program, in its memory management functions, can easily experience dramatic drops in CPU utilization rates due to the heavy lock contention introduced by a non-scalable heap design. MTS usually leads to an overall application performance improvement of 30-50%, and gains of between 800-1200% are common.

http://www.newcodeinc.com/
http://www.mathtools.net/C_C__/Memory_management/

Sparse Grid Interpolation Toolbox
The Sparse Grid Interpolation Toolbox is a MATLAB toolbox for recovering expensive, possibly high-dimensional multivariate functions. It includes hierarchical sparse grid interpolation algorithms based on both piecewise multilinear and polynomial basis functions.

http://www.ians.uni-stuttgart.de/spinterp/
http://www.mathtools.net/MATLAB/Mathematics/Fitting_and_Interpolation/

E-DSP: Electronic and DSP Projects
E-DSP is a Web site for learning elementary electronics and DSP, and applications on Xilinix FPGA, as well as MCUs from Atmel and Microchip.

http://www.e-dsp.com/
http://www.mathtools.net/Applications_and_Industries/DSP/Tutorials/

More Free Webinars:


Introduction to Simulink for Control Design
This webinar, to be broadcasted on March 9, is an introduction to Simulink for control design. It will introduce key features in Simulink and the Simulink product family that enable you to build sophisticated controllers in an integrated workflow. Through product demonstrations, attendees will see a high-level overview of the major capabilities, and learn how to design, simulate, implement, and test, control systems all within the Simulink environment.

http://www.mathworks.com/programs/mathtools/feb06/slcda/index.html

Developing Software Defined Radio Software Systems Using MATLABŪ and SimulinkŪ
Join us on March 16 to learn how to use the Simulink family of products in Software Defined Radio (SDR) applications. This presentation uses real-time demos to demonstrate how Model-Based Design using Simulink tools enables developers of SDRs to progress through successive stages of radio development.

http://www.mathworks.com/programs/mathtools/feb06/radio/index.html

Developing Wireless Systems with MATLAB and Simulink
In this webinar, to be broadcast live on March 30, you will learn how you can use Model-Based Design with the MATLABŪ and SimulinkŪ product families to quickly and accurately convert a wireless standards document on paper into an executable specification. Using the IEEE 802.11b wireless LAN physical layer standard as an example, we will demonstrate how to model key signal processing subsystems, including techniques for modeling frames and handling rate

http://www.mathworks.com/programs/mathtools/feb06/dws/index.html


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