Open Source MATLAB Information Analysis Software

LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone.

The purpose of this program is to teach a computer to classify plants via their leaves. You just need to input the image of a leaf(acquired from scanner or camera), then the computer can tell you what kind of plant it is.

Source code from the Research Institute for Signals, Systems and Computational Intelligence http://fich.unl.edu.ar/sinc

The Databionics ESOM Tools offer many data mining tasks using Emergent Self-Organizing Maps. Visualization, clustering, and classification of high-dimensional data using databionics principles can be performed interactively or automatically.

Version 1.1 is no longer supported. Please see the new version at https://usc-imi.github.io/aeo-light/ Description for 1.1 continues below: AEO-Light 1.1 is an open-source software application that takes a digital scan of motion picture film with optical sound tracks and directly reproduces the audio, producing as a result a synchronized sound film file. Funded by a grant from the National Endowment for the Humanities and by the University of South Carolina.

An implementation of the Kernel-based Orthogonal Projections to Latent Structures (K-OPLS) method for MATLAB and R. The supplied functionality includes e.g. cross-validation, kernel parameter optimization, model diagnostics and plot tools.

The OARS app is a data logger developed to run on Android OS and devices containing an internal GPS ,along with micro-electro-mechanical systems (MEMS) chipset. Specifically the Invensence MPU-6000 or newer. This chip is a highly accurate inertial measurement unit, or (IMU). Contained within this small IMU is a 3-axis Accelerometer, 3-axis Gyro, and 3-axis Magnetometer. Along with a built in processor, it can calculate movements along 9-axis. Depending on platform and app setting, OARS can record sensor values at a rate up to 100hz, or 100 positions per second. GPS data such as Longitude, Latitude, Direction, Speed, and Elevation, are also logged at approximately 1hz, or 1 update per second. Giving you the ability to precisely map an equipped objects location, orientation, and rate of movement along any plane with extreme accuracy.

Design and develop Recommendation and Adaptive Prediction Engines to address eCommerce opportunities. Build a portfolio of engines by creating and porting algorithms from multiple disciplines to a usable form. Try to solve NetFlix and other challenges.

The Multivariate Regression Composer, a Matlab toolbox. It generates a regression model of the optimal structure. Uses the source data set, the initial models and the primitive functions.

NSB entropy and mutual information estimator; applications to the analysis of neural code.

This is a Matlab software package for single molecule FRET data analysis.

This is the prototype version of software for robust detecting and segmentation of cell nuclei in 3D fluorescence labeled microscopy images. First release coming soon...

Framework for uncertainty propagation in predictive models targeted for collaborative science

This site provides the source code of two approaches for density-ratio based clustering, used for discovering clusters with varying densities. One approach is to modify a density-based clustering algorithm to do density-ratio based clustering by using its density estimator to compute density-ratio. The other approach involves rescaling the given dataset only. An existing density-based clustering algorithm, which is applied to the rescaled dataset, can find all clusters with varying densities that would otherwise impossible had the same algorithm been applied to the unscaled dataset. Reference: Zhu, Y., Ting, K. M., & Carman, M. J. (2016). Density-ratio based clustering for discovering clusters with varying densities. Pattern Recognition. http://www.sciencedirect.com/science/article/pii/S0031320316301571

Matlab freeware for data analysis, by J. M. Lilly

MATLAB Audio Database Toolbox enables easy access and filtering of audio databases such as TIMIT and YOHO by their metadata. The database toolbox comes to replace the manual filtering and custom coding usually required for accessing such databases.

Implematation of robust depth-based inference tools for microarray data (a scale curve, to measure the dispersion of a set of curves, a rank test to decide if two groups of curves come from the same population, and classification techniques).

The main goal of this project is to develop new algorithms of machine learning and collect examples of existing methods. This collection pursues scientific and educational purposes.

Audio spectrum analyzer in software module and a hardware module to display the spectrum.

BRAHMS is a Modular Execution Framework for dynamical systems. It knits together independently-authored software modules implementing dynamical processes into an integrated system, and supervises the deployment and execution of that system.

Bayesian Surprise Matlab toolkit is a basic toolkit for computing Bayesian surprise values given a large set of input samples. It is also useful as way of exploring surprise theory. For more information see also: http://ilab.usc.edu/

Visualization and clustering analysis of X-Ray diffraction data from combinatorial thin film libraries.

CoRoPa stands for Computational Rough Paths. The aim of CoRoPa is to provide a software framework for various ideas related to Rough Path Theory, including rough differential equations and the digital description of serial data streams.

This is a MATLAB toolbox for the quality control and scoring of EMAP and SGA genetic interaction data. It includes a graphical user interface and some automatic plot-generating tools.

Functional Mechanism is a differentially private method designed for a large class of optimization-based analyses. The main idea is to enforce epsilon-differential privacy by perturbing the objective function of the optimization problem, rather than its results. Please cite the following paper if you choose to use this code: J. Zhang, Z. Zhang, X. Xiao, Y. Yang, and M. Winslett. Functional Mechanism: Regression Analysis under Differential Privacy. PVLDB 5(11):1364-1375, 2012.