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Using hedge fund data as an example, this article demonstrates how MATLAB® can be used to automate the process of acquiring and analyzing fraud detection data.
A process for real options valuation of an iron ore mine, including developing price and interest-rate models based on historical data, and producing distributions for a range of economic outcomes based on calculations of net present value (NPV).
TrueAllele technology uses MATLAB, Signal Processing Toolbox, and Statistics Toolbox to mathematically separate mixed DNA data into individual contributors and their respective genotypes.
Topics covered include assessing code performance, adopting efficient serial programming practices, working with System objects, performing parallel computing, and generating C code.
Using Simulink models and physical structures, Lehigh University researchers test reactions to seismic activity in ships’ hulls, bridge decks, shear walls, and four-story buildings.
MATLAB image processing and statistical analyses give researchers an objective computational method for measuring the ability of drugs in development to inhibit cancer metastasis.
MATLAB and Simulink models help Simon Fraser University researchers run and control experiments to determine how sensory input affects walking speed.
Developed in MATLAB, Sonarscope software lets researchers process, analyze, and visualize terabytes of raw MBES data.
Using WMS to simplify the process of finding geospatial raster data and Mapping Toolbox to analyze the data and create map displays.
A MATLAB based model helps analysts project the future state of the New Zealand economy.
This freshman seminar gives students practical experience in geological and geophysical research using MATLAB.
Using MATLAB®, Capgemini has developed a process for calculating economic capital that takes portfolio concentration into account.
University of Illinois researchers use advanced statistical methods to explain how changes in climate affect the ecosystem and how human changes to landscape affect the regional climate.
This article demonstrates a workflow that uses built-in functionality in MATLAB® and related products to develop a classification algorithm for an isolated, speaker-dependent speech-recognition system.
To determine whether the wing design of a small passenger aircraft meets strength requirements, we derive analytical models of the loads and bending moments on the wing using the notebook interface in Symbolic Math Toolbox.
Using an aerospace system model as an example, this article describes the parallelization of a controller parameter tuning task using Parallel Computing Toolbox and Simulink Design Optimization.
This article describes two ways to use parallel computing to accelerate the solution of computationally expensive optimization problems.
Applying object-oriented techniques improves your ability to manage software complexity–particularly important when developing and maintaining large applications and data structures.
New scenario analysis models enable Italy’s leading bank to comply with Basel II requirements by holding capital against losses arising from operational risk.
This article discusses how researchers at UC San Francisco and UC Davis analyzed high-resolution microscopy images of cells using MATLAB, Statistics Toolbox and Image Processing Toolbox.
Use these tools and techniques to create designs that perform as expected over time and are insensitive to changes in manufacturing, operational, or environmental factors.
Analyzing array-based comparative genomic hybridization data.
In the summer of 2002, flooding in Europe caused billions of Euros in damage. Five years earlier, a 75% drop in the Thai stock market contributed to a 554-point drop in the Dow Jones Industrial Average on October 27, 1997.
Every real-world system operates under uncertainty and failure to account for that uncertainty can lead to inaccurate predictions of system behavior.
Engineers and scientists use a variety of approaches to improve or design quality into products.
Interactive visualization tools help implement advanced statistical techniques for analyzing batch processes.

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