Fast and multi platform reader of network traces, have possible to shared date in screen, file or Matlab
A collection of MATLAB tools for PIV, PTV, particle sizing, and more.
Qi is a collection of MATLAB tools for the quantitative analysis of flow field images. Our Particle Image Velocimetry (PIV) tool, prana, implements a Robust Phase Correlation kernel for PIV analysis, and now includes Particle Tracking Velocimetry and sizing tools. Tools for pressure calculation, proper orthogonal decomposition (POD), and 3d imaging are under development.
Cross platform electromagnetics finite element analyisis based on FEMM
Cross platform electromagnetics finite element analysis code, with very tight integration with Matlab/Octave. xfemm is a refactoring of the core algorithms of the popular Windows-only FEMM (Finite Element Method Magnetics, www.femm.info) to use only the standard template library and therefore be cross-platform. The codes can be used as a library, standalone executables, or through the advanced Matlab/Octave interface, which uses direct data exchange at the memory level rather than the original FEMM ActiveX or file-based interface, for much improved communication speed. If you use xfemm, particularly for industrial work, but also academic, it will be greatly appreciated if you could write an email stating this and how it has supported your work. This is a low-cost way to ensure further development and maintenance will continue! Contact me on the discussion forum for more information.
Tools for mass spectrometry, especially for protein mass spectrometry and proteomics: Quantification tools, converters for Applied Biosystems (Q Star and Q Trap), calculation of in-silico fragmentation spectra, converter for Mascot result files
Matlab freeware for data analysis, by J. M. Lilly
The Biopsychology Nonlinear Toolbox is a MATLAB toolbox that combines established analysis routines in one easy to use graphical user interface.
This projected is designed for the rapid identification and analysis of the D-Period spacing in collagen fibrils.
Glycosylation Network Analysis Toolbox (GNAT)
GNAT is an open source, platform-independent MATLAB based toolbox. It is written in MATLAB and Java. It has been tested in Windows (Windows 7), Linux (Ubuntu), and Mac OS (X Lion) platforms. The original GNAT package (file GNAT.zip) provides functions for reading, writing, manipulation, visualization and simulation of glycan structures and glycosylation reaction networks (citation ). The second version of this software (GNATv2beta.zip) upgrades the original GNAT program with additional features that are geared towards incorporating glycan-structure experimental data into the simulation environment. For information about GNAT installation and usage, please see the GettingStarted.pdf file enclosed in the package. To cite GNAT:  Gang Liu, Apurv Puri and Sriram Neelamegham, Glycosylation Network Analysis Toolbox (GNAT): a MATLAB based environment for systems glycobiology, Bioinformatics 2013 29: 404-406
Extended Marcatili method for Rectangular Waveguides in Matlab
We recently extended Marcatili’s approximate analytical approach for the description of light propagation in rectangular waveguides to the regime of (silicon) high-index-contrast waveguides. This software is a Matlab implementation of the method.
Advanced vehicle simulator
This project holds the latest releases for canonical versions of the ADVISOR® Software and "Advanced Vehicle Simulator". ADVISOR is a MATLAB/Simulink based simulation program for rapid analysis of the performance and fuel economy of light and heavy-duty vehicles with conventional (gasoline/diesel), hybrid-electric, full-electric, and fuel cell powertrains. New features are developed under the title "Advanced Vehicle Simulator". Periodically, stable versions of Advanced Vehicle Simulator will be submitted for consideration as the next canonical version of the ADVISOR software. ADVISOR is a registered trademark of the Alliance for Sustainable Energy, LLC, the manager and operator of the National Renewable Energy Laboratory for the United States Department of Energy. Trademark used under license.
Locally Weighted Projection Regression (LWPR)
Locally Weighted Projection Regression (LWPR) is a fully incremental, online algorithm for non-linear function approximation in high dimensional spaces, capable of handling redundant and irrelevant input dimensions. At its core, it uses locally linear models, spanned by a small number of univariate regressions in selected directions in input space. A locally weighted variant of Partial Least Squares (PLS) is employed for doing the dimensionality reduction. Please cite:  Sethu Vijayakumar, Aaron D'Souza and Stefan Schaal, Incremental Online Learning in High Dimensions, Neural Computation, vol. 17, no. 12, pp. 2602-2634 (2005).  Stefan Klanke, Sethu Vijayakumar and Stefan Schaal, A Library for Locally Weighted Projection Regression, Journal of Machine Learning Research (JMLR), vol. 9, pp. 623--626 (2008). More details and usage guidelines on the code website.
This project is a lab prototype of MEG default mode network in MATLAB.
Default mode network (DMN) or task negative network (TNN) may provide useful information on state of brain. Normal brain is constantly busy and demonstrates a network of synchronized activity at distinct brain regions. Trauma, injury, or resection ruptures this natural network of neuronal connectivity, subsequently altering the default scheme of synchronized activation. This utility is designed to quickly analyze and visualize the default mode network, at current state of brain, for MEG data acquired from any subject. Customization of threshold and sampling rate, followed by complete circular visualizations for quick clinical references are a plus. The program is primarily designed to facilitate clinicians, and researchers. The researchers can further analyze, if required, using the MAT file stored from the last analysis. Moreover, the framework can be used to estimate functional connectivity while performing any particular task.
Routines for wavefront propagation in IDL, Matlab, and Python
PROPER is a library of routines for the propagation of wavefronts through an optical system using Fourier-based methods. It was developed at the Jet Propulsion Laboratory for modeling stellar coronagraphs, but it can be applied to other optical systems were diffraction propagation is of concern. It is currently available for IDL (Interactive Data Language), Matlab and Python (2.7 & 3.x). It includes routines for generating complex apertures and obscurations and aberrations (Zernike & PSD-defined). It includes a model of a deformable mirror for wavefront control. The routines perform near and far field propagation with automatic selection of propagators. The latest version for IDL and Python is v3.0 released on 7 Aug 2017. For Matlab it is v3.0.1 released on 22 Aug 2017 (bug fix in prop_readmap).
Different LDPC Libraries for DVB-T2/S2
Provides more than one different set of LDPC encoder and decoder, mainly to work with the DVB-T2 Common Simulation Platform Be sure to read the Wiki!
Version 1.1 is no longer supported.
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.
Satellite Power Analysis Tool
# Satellite Power Analysis Tool (SPAT) The tool was originally created to aid during the Satellite Power System design process, however it has evolved to a Satellite Missoin design tool. The user defines the mission and the Satellite design paramenters and, the tool will output: - Power analysis - Battery charge/discharge analysis - Link budget - Ground track coverage - Ground station visibility SPAT has been developed in MATLAB and MCR (Matlab runtime) is required. SPAT is pre-compiled and currently available for MacOS and Windows email: aitorvs(AT)gmail.com
Fingerprint Recognition System 5.3 - Matlab source code
The proposed filter-based algorithm uses a bank of Gabor filters to capture both local and global details in a fingerprint as a compact fixed length FingerCode. The fingerprint matching is based on the Euclidean distance between the two corresponding FingerCodes and hence is extremely fast. We are able to achieve a verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms published in the open literature. Our system performs better than a state-of-the-art minutiae-based system when the performance requirement of the application system does not demand a very low false acceptance rate. Finally, we show that the matching performance can be improved by combining the decisions of the matchers based on complementary (minutiae-based and filter-based) fingerprint information. Index Terms: Biometrics, FingerCode, fingerprints, flow pattern, Gabor filters, matching, texture, verification.
Face Recognition System Matlab source code
Research on automatic face recognition in images has rapidly developed into several inter-related lines, and this research has both lead to and been driven by a disparate and expanding set of commercial applications. The large number of research activities is evident in the growing number of scientific communications published on subjects related to face processing and recognition. Index Terms: face, recognition, eigenfaces, eigenvalues, eigenvectors, Karhunen-Loeve algorithm.
URBI: Universal Robotic Body Interface. URBI is a scripted command language used to control robots (AIBO, pioneer,...). It is a robot-independant API based on a client/server architecture. Liburbi C++/Java/Matlab are available here. Forum available at ht
The Dutchroll project provides Open Source applications for Matlab and Simulink, with the emphasis on aerospace engineering. The main application is the Flight Dynamics and Control toolbox; other applications will be derived from that toolbox.