Open Source MATLAB Software Development Software - Page 4

This software is a java3d-based grid platform and depends on jvm and matlab.

A design paradigm and corresponding enabling technologies, in which sensing and comms systems are integrated to efficiently utilize congested wireless/hardware resources, and even to pursue mutual benefits. Waveform Design and Signal Processing Aspects for Fusion of Wireless Communications and Radar Sensing. Supported by IEEE ComSoc ISAC Emerging Technology Initiative (ETI). Integrating Sensing and Communications for Ubiquitous IoT. Include reproducible codes, good papers and a research libary.

The NUMIPAD library implements several methods/algorithms to solve inverse problems and adaptive decomposition (i.e. Tikhonov regularization, Total Variation, Basis Pursuit, etc.)

NeMo is a high-performance spiking neural network simulator which simulates networks of Izhikevich neurons on CUDA-enabled GPUs. NeMo is a C++ class library, with additional interfaces for pure C, Python, and Matlab.

The NJ toolbox (njTBX) is a matlab object API, built on top of Unidata's Netcdf-Java API to facilitate netCDF model data manipulation. Development of njTBX is a part of 'An Open-Source Community Model for Coastal Sediment Transport' project.

The project goal is to develop several IP cores that would implement artificial neural networks using FPGA resources. These cores will be designed in such a way to allow easy integration in the Xilinx EDK framework.

The class libraries here provide infrastructure for creating simulations of low energy nuclear physics experiments, as well as some useful working programs that do simple simulations and analysis of experiments performed with magnetic spectrographs.

Octave Workshop is an integrated development environment for the GNU Octave programming language.

Octave development environment built upon Eclipse's Dynamic Languages Toolkit (http://www.eclipse.org/dltk/). Distributed as an Update site for Eclipse 3.7 Indigo and Indigo-based package for several platforms. Supports search, autocompletion, launching scripts, interactive console, debug and integrated plotting on Octave versions 3.2.x, 3.4.x and 3.6.x. The current goal is to make it running out-of-box on multiple platforms. Currently only Linux and Windows are supported. Mac support is possible. The project needs a maintainer for Mac version, since I don't have Mac to build Octclipse and test it on this platform. Also, it is worth to support Eclipse 4.0 Juno with DLTK 4.

This repository hosts the Omniglot dataset for one-shot learning, containing handwritten characters across multiple alphabets along with stroke data. It includes both MATLAB and Python starter scripts (e.g. demo.m, demo.py) to illustrate how to load the images and stroke sequences and run baseline experiments (such as classification by modified Hausdorff distance). The dataset provides both an image representation of each character and the time-ordered stroke coordinates ([x, y, t]) for each instance. Includes stroke data (time-sequenced coordinates) per sample. The repository is intended as a benchmark dataset in few-shot / meta-learning research, not as a plug-and-play detection or classification engine. Pre-split “background” and “evaluation” alphabets for standard benchmarking.

Online Signature Verification technology requires primarily a digitizing tablet and a special pen connected to the USB port of a computer. An individual can sign on the digitizing tablet using the special pen regardless of his signature size and position. The signature is characterized as pen-strokes consisting x-y coordinates and pressure with the data being stored in a signature database. Dynamic time warping (DTW) and quadratic discriminant analysis (QDA) is used to get results where the system accepts 2% of forged signatures and rejects 5% of true signatures

OpenOpt is FREE (GNU GPL v.2) MATLAB/Octave toolbox, powered by user-contributed solvers & ideas. Scaling, updating counters etc is performed by OpenOpt BaseModule. Local & global solvers, easy interface, possibility of graphical output, etc, etc. Enjoy

We present the package Optimizer, aimed at constructing and optimizing general mathematical models of phenomena of versatile nature. It is written in the Matlab algorithmic language and is executed in the Matlab environment with partial functionality in Octave. The convenient visual interface and the detailed manuals are provided. The main benefit of the package is its capability to construct models of any level of complexity in a block-by-block manner. Elementary model blocks can be collected in libraries, and we have already written many such library programs. Many of these programs are already available along with the main package. Currently, the main focus of these is computational quantum mechanics, analysis and simulation of molecular spectra, and general-purpose approximants. The package provides the most reliable modern strategies for linear and non-linear model optimization, regularization, and hypothesis tests. Parallel computing is supported.

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.

Rust numeric library contains linear algebra, numerical analysis, statistics and machine learning tools with R, MATLAB, Python-like macros. Peroxide uses a 1D data structure to represent matrices, making it straightforward to integrate with BLAS (Basic Linear Algebra Subprograms). This means that Peroxide can guarantee excellent performance for linear algebraic computations by leveraging the optimized routines provided by BLAS. For users familiar with numerical computing libraries like NumPy, MATLAB, or R, Rust's syntax might seem unfamiliar at first. This can make it more challenging to learn and use Rust libraries that heavily rely on Rust's unique features and syntax.

PeterHi is an initiative to provide a set of tools for education based on your existing IT infrastructure.

Create interactive charts in your web browser with MATLAB® and Plotly.

PopED (Population Experimental Design) is a software tool for computing optimal experimental designs. The software has been developed with an emphasis on drug trials based on population models (non-linear mixed effects models).

software educativo de aplicacion de metaheuristicas sobre problemas de grafos, TSP problema del agente viajero, ruta mas corta, arbol de expansion minima, etc.

An Initiative to help the Engineering & Research Community

Linux ERT target controls code generation from Simulink for computer based on MPC5200 and Linux. The target contains support for CANopen via Simulink blockset which integrates the CANopen driver to the generated code.

This toolbox is a collection of MatLab functions for reading WinView/WinSpec files (.spe extension) directly to MatLab. It provides functions for reading full header from file into a structure, reading frames into matrices, and reading pixel values across all frames. You can use these functions to analyse and process experiment data stored in .spe files in MatLab, and to write functions to export .spe files to animated GIFs for use in presentations. Also includes simple MatLab application for converting files to GIF, AVI and .spe files, and provides functionality for quick addition of support for WinView-like formats by users, without the need to call developers.

These classes are useful for signal processing in Matlab or C++. They bring together tools and methods which may be used interchangeably for Matlab and C++. Their initial use is in conjunction with work towards my degree at UC Berkeley.

Smart-Algorithm is a repository implementing a variety of intelligent / metaheuristic optimization algorithms (e.g. Genetic Algorithm, Ant Colony, Particle Swarm, Immune Algorithm). The implementations are provided in multiple languages (Java, Python, MATLAB). The repository’s aim is to offer reference implementations of “smart” algorithms for tasks like route planning, optimization, or algorithm learning. Particle Swarm Optimization (PSO) implementations in multiple languages. Immune Algorithm (or immune-inspired optimization) implementations. Multiple versions/language compatibility (Java, Python, MATLAB).

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.