Open Source MATLAB Software Development Software for Linux

Octave Forge is a central location for collaborative development of packages for GNU Octave. The Octave Forge packages expand Octave's core functionality by providing field specific features via Octave's package system. See https://octave.sourceforge.io/packages.php for a list of all available packages. GNU Octave is a high-level interpreted language, primarily intended for numerical computations. It provides capabilities for the numerical solution of linear and nonlinear problems, and for performing other numerical experiments. It also provides extensive graphics capabilities for data visualization and manipulation. Octave is normally used through its interactive command line interface, but it can also be used to write non-interactive programs. The Octave language is quite similar to Matlab so that most programs are easily portable. Refer to https://www.octave.org for more information.

This Matlab package implements machine learning algorithms described in the great textbook: Pattern Recognition and Machine Learning by C. Bishop (PRML). It is written purely in Matlab language. It is self-contained. There is no external dependency. This package requires Matlab R2016b or latter, since it utilizes a new Matlab syntax called Implicit expansion (a.k.a. broadcasting). It also requires Statistics Toolbox (for some simple random number generator) and Image Processing Toolbox (for reading image data). The code is extremely compact. Minimizing code length is a major goal. As a result, the core of the algorithms can be easily spotted. Many tricks for speeding up Matlab code are applied (e.g. vectorization, matrix factorization, etc.). Usually, functions in this package are orders faster than Matlab builtin ones (e.g. kmeans). Many tricks for numerical stability are applied, such as computing probability in logrithm domain, square root matrix update to enforce matrix symmetry.

Create GTK+ interfaces using IOStream style code. Its simple and quick! Also providing simple data plotting (similar to Matlab/Octave), ORB (Object Request Broker), and Neural Network computations. You can create GTK+ GUIs in a few lines of code. Labels<<"Thanks for reading"; (HBox<<Labels).show(); or even one line : (HBox() << (Labels()<<"Thanks for reading")).show(); Inline code destructs the classes, but leaves the widgets/callbacks operating. This is great for embedded memory saving code. You can also plot like so : Plot figure; figure.plot(x, y, x.size()); Plotting utilises GtkDataBox.sf.net ORB utilises www.zeroc.com Feed forward neural networks with different activation functions. Audio playback/recording and digital signal processing (DSP) - utilising Jack www.jackaudio.org

Implementation of duration high-order hidden Markov model (DHO-HMM) in Matlab with application in speech recognition.

Matlab Toolbox to process video files, which consists on a set of classes for reading, writing, correcting light changes and generating gaussian pyramids in real time. This toolbox is designed for Windows x64, Max OS X x64 and Linux x64. Through to use of Ffmpeg, it can reproduce and create videos very fast and also do no require to load the entire video file in memory. In addition the C++ code is already compiled in order to simplify the toolbox installation. In order to stay tuned for updates, you can follow the Matlab VideoUtils on Twitter (@VideoUtils): https://twitter.com/#!/VideoUtils If anyone is interested in collaborate, please contact to me -> https://sourceforge.net/sendmessage.php?touser=3811831

AVRS performs spatial 3D-sound processing allowing the arbitrary placement of sound source in auditory space. The main goal is to develop a genuine experimental flexible platform, that runs in a general-purpose architecture computer (standard hardware and software).

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.

MatImage is a Matlab library for image processing and analysis in 2D and 3D. It contains more than 250 fonctions for image enhancement, filtering, analysis, or visualisation, as well as for creating basic test shapes. It is built as a complement of the Mathworks image processing toolbox (IPT). Project is being transfered to GitHub: http://github.com/dlegland/matImage

This package can be used for further development of package needs to deal with 3D geometrical relationship. It provides class for Vector, Point, Coordinate, transformations and also provides functions for dealing with relationships between them.

FAMOUSO is an event-based publish/subscribe middleware written in C++ for systems ranging from 8Bit micro-controllers up to 32Bit PC/Workstations.

Thank you for your interest in Speedy Composer. Speedy Composer is an automated application for composing melodies for Speedy Net members. We recently made changes to the source code of Speedy Net, and converted it into the Python language and Django framework. Since Speedy Composer was originally written in PHP, it is not adapted to work with Speedy Net in its current form. So unfortunately we were forced to temporarily close the app Speedy Composer. But don't worry, we kept backups of all the tunes composed by Speedy Composer, and when the website is reopened we will upload them to the new site. Speedy Composer and Speedy Net are open source applications, free software. We are currently looking for volunteers to help us convert Speedy Composer to Python. If you are interested in volunteering, please contact me by email. Thank you and good luck, Uri Rodberg Founder and Director of Speedy Net and Speedy Composer, Speedy Paz Technologies Ltd. uri@speedy.net

libGo is a C++ class library containing all kinds of things that proved useful to me. Included are: - Linear algebra, using LAPACK and CBLAS - V4L(1) image grabber - Multithreading - Image containers (up to 3D) - Some simple optimisation code - Python embedding helper - Matlab interface - .. and other things, have a look at the HTML documentation! golib grew over many years, things I had use for have been added now and then. Some parts are better taken care of than others. If you find anything spectacularly wrong or badly documented, and need assistance, please drop me a line.