This zip describes SPI communication with a Serial DataFlash AT45DB and/or with a DataFlashCard AT45DCB. It shows how to configure the SPI peripheral on the AT91RM9200EK. Includes main.html file for help. For use under Green Hills 3.6.1 Multi?2000 Software Tool
This zip describes an AT91 USART with PDC Transmission and Reception chain.Includes main.html file for help. For use under Green Hills 3.6.1 Multi?2000 Software Tool.
This a simple genetic algorithm implementation where the
evaluation function takes positive values only and the
fitness of an individual is the same as the value of the
objective function
annie is an ANN, ie, Artificial Neural Network library developed in C++. It can be used to implement various kinds of neural networks like Multi-Layer Perceptron, Radial basis function networks, Hopfield networks etc.
Single-layer neural networks can be trained using various learning algorithms. The best-known algorithms are the Adaline, Perceptron and Backpropagation algorithms for supervised learning. The first two are specific to single-layer neural networks while the third can be generalized to multi-layer perceptrons.
人工智能中模糊邏輯算法
FuzzyLib 2.0 is a comprehensive C++ Fuzzy Logic library for constructing fuzzy logic systems with multi-controller support.
It supports all commonly used shape functions and hedges, with full support for the various types of Aggregation, Correlation, Alphacut, Composition, Defuzzification methods.
The latest version of the C++ Fuzzy Logic Class Library contains all the C++ source code and comes complete with a usage example for building a multi-controllers fuzzy logic model.
Welcome to PMOS. PMOS is a set of modules, mostly written in Modula-2,
to support multitasking. PMOS was designed primarily with real-time
applications in mind. It is not an operating system in the conventional
sense rather, it is a collection of modules which you can import
into your own programs, and which in particular allow you to write
multi-threaded programs.
A program to demonstrate the optimization process of particle swarm optimization. A two-dimensional objective function is visualized by level of grey: the lighter the color, the higher the function value. The particles are shown as red circles, their trajectory as red lines.
