Open Source Server Operating Systems Algorithms

* Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive Apache 2.0 license, useful for both open-source and proprietary (closed-source) software * Can be used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc * Downloads: http://coot.sourceforge.io/download.html * Documentation: http://coot.sourceforge.io/docs.html * Bug reports: http://coot.sourceforge.io/faq.html * Git repo: https://gitlab.com/conradsnicta/bandicoot-code

This project uses massively parallel Graphics Processing Units(GPU) for neural network(Backpropagation) purposes.

GEP is an evolutionary algorithm for function finding. This framework is a powerful way of expressing and coding genetic-like structures and quickly finding solutions through evolution by common genetic operators.

darknocK detects edges in images. It is using Artificial Neural Networks to enchance the results of standard algorithms.

This project comprises two main parts: 1. The classic "Rodney" as described in David L. Heisermann's book "How to build your own self-programming robot", with the original Intel 8085 code. In all likelihood, this is for reference only. I don't expect many people are going to build it 2. An updated version, running on more modern hardware, but remaining true to the algorithms published in his book. The end result will be at least three sets of code, for the Alpha, Beta and Gamma versions of Rodney. We would also like to experiment with a "Delta" version which could use either bare RF or WiFi to exchange state data between machines. A "hive mind" if you like. For the new-generation version, we propose targeting two hardware platforms: 1. Arduino, since it's cheap and easy to use, while remaining close to the bare metal 2. A purpose-built AVR card, or easily ported to cards obtainable from sources such as futurlec.com, etc. RaspberryPi is also an option later