Open Source Algorithms - Page 20

This project is no longer supported. We are working on a new algorithmic trading platform with extreme fast execution speed and lots of cool features. Please visit http://www.algospace.com/ for more detail.

AlgoExplorer is a dynamic data structures viewer for Java. It allows the visualization of data structure of a Java program, allowing you to see how objects, handled by the algorithms, interact with each other and how they are related and linked. The project has been moved on: http://code.google.com/p/algoexplorer/

The Aim of this project is to provide a collection of reusable Algorithms which can be used effectively in different scenarios. Algorithm implementations are in Java. Objective here is to implement algorithms which should be more efficient than the JDK implementation and also to create a platform for the researchers who works on Data Mining, Encryption algorithms, ect.. to collaborate and contribute to this project.

An Algorithm Library written in .Net 2.0 which includes common algorithms.

An algorithm is represented by a .h file and placed under include. (one .header file per algorithm.) The demo program for the algorithm demonstration is placed under src. (one demo per algorithm.) After the program passes correctly, please initiate Pull Requests, the code is verified and stored in the library, and the new algorithm implementation is published in the README. TAB = 4 space. set ts=4 in vim. Graph output format is Graphviz Dot format. (the output format of the graph is in dot of graphviz.)

Provide implemented algorithms and functions with demo programs to test.keeped portable as possible at OS level and programming language(understanding)level.provide third party archives if available for ralvent algorithm.links for YouTube videos on availability by us and third party.

This will help a new data structure learner to learn data structures quickly.

This code is the translation into C++ of part of the Matlab code from Mark Veillette available at: http://www.mathworks.com/matlabcentral/fileexchange/37514-stbl--alpha-stable-distributions-for-matlab

AlphaTensor, developed by Google DeepMind, is the research codebase accompanying the 2022 Nature publication “Discovering faster matrix multiplication algorithms with reinforcement learning.” The project demonstrates how reinforcement learning can be used to automatically discover efficient algorithms for matrix multiplication — a fundamental operation in computer science and numerical computation. The repository is organized into four main components: algorithms, benchmarking, nonequivalence, and recombination. These contain implementations of the discovered matrix multiplication algorithms, tools to benchmark their real-world performance, proofs of nonequivalence among thousands of solutions, and methods for decomposing larger problems into smaller factorizations. Users can explore AlphaTensor’s discovered algorithms interactively using Colab notebooks or Python scripts.

A .Net library coded in C# language that inplements some sort of functions I found useful.

The Gene Expression Programming Framework in Java. It separates the process of evolution from the process of interpretation of the chromosome, allowing the use of various schemes in the chromosome.

A complete library of high-speed java collection classes to complement existing classes with new and advanced algorithms. Complements standard J2SE classes and Jakarta commons classes

The purpose of the project is summarising effort from a number of analytic libraries, adding interactive web-based user interface and making a free open source solution for risk analytics and stress testing. Feb 8, 2012 Paul Glasserman's Importance Sampling and Tail Approximations as well as plain Monte Carlo have been implemented for for the widely used normal copula model of portfolio credit risk. The package includes source code, examples, spreadsheet with results and references to the papers.

The main goal of the Analytical Customer Relationship Management system is to improve services provided to customers, and to use customer contact information for targeted marketing.

Este proyecto constituye una adaptacion y mejora del codigo ANFIS de dominio público de Roger Jang. / This project is an adaptation and improvement of the original public domain ANFIS code of Roger Jang.

Animal is a Java-based system for visualizing and animating algorithms and data structures. Available since 1999, it is one of the established AV systems, and provides one of the largest collections of supported algorithms. Animations can be generated on the fly based on user input - for a large selection of algorithms and topic areas, including, but not limited to, the topic areas of backtracking algorithms, compression, cryptography, basing, searching and sorting.

Animants are virtual ants. Their name comes from the combination of "ants" and "animats", an animat being "a sofware approximation of a living creature". Animants aim to simulate the behaviour of living animals.

An interactive binary search tree. The user may interact with the tree by performing rotations, balancing, insertions, and deletions. For educational purposes

Delphi library of standard containers for keeping ordinal and structured datatypes.

Our aim is to create a collection of useful and free Ansi C libraries of code that are portable around systems.

The subgraph matching problem (subgraph isomorphism) is NP-complete. Previously, we designed an exact subgraph matching (ESM) algorithm for dependency graphs using a backtracking approach (http://esmalgorithm.sourceforge.net). We further designed an approximate subgraph matching (ASM) algorithm that is capable of detecting approximate subgraph matching based on a subgraph distance. Assume that the graph G and the subgraph Gs have m and n vertices, and km and kn edges respectively, the total worst-case algorithm complexity is O(m^n * n(n-1)/2 * km * log m). This Java implementation implements our ASM algorithm. See README file: https://sourceforge.net/projects/asmalgorithm/files/ If you use our ASM implementation to support academic research, please cite the following paper: Haibin Liu, Lawrence Hunter, Vlado Keselj, and Karin Verspoor. Approximate Subgraph Matching-based Literature Mining for Biomedical Events and Relations. PLOS ONE, 8:4 e60954, 2013.

Arageli is a C++ library for computations in arithmetic, algebra, geometry, linear and integer linear programming. Arageli provides routines and classes that support precise, i.e. symbolic or algebraic, computations.

The Arbitrarily-Decomposed MPI FFT library is a C subroutine library for the computation of the multidimensional Fast Fourier Transform (FFT) of a distributed grid using the Message-Passing Interface (MPI).

We live in very exciting times 😃! BLDC motors are entering the hobby community more and more and many great projects have already emerged leveraging their far superior dynamics and power capabilities. BLDC motors have numerous advantages over regular DC motors but they have one big disadvantage, the complexity of control. Even though it has become relatively easy to design and manufacture PCBs and create our own hardware solutions for driving BLDC motors the proper low-cost solutions are yet to come. One of the reasons for this is the apparent complexity of writing the BLDC driving algorithms, Field oriented control (FOC) being an example of one of the most efficient ones. The solutions that can be found online are almost exclusively very specific for certain hardware configurations and the microcontroller architecture used. Additionally, most of the efforts at this moment are still channeled towards the high-power applications of the BLDC motors and proper low-cost FOC.