Neural Fuzzy

AnimatLab is a simple, easy to use application specially designed to combine biomechanical simulation and biologically realistic neural networks. You can build the body of an animal, robot, or other machine and place it in a virtual world where the physics of its interaction with the... Platforms: Windows

DynNet is built as a Java library that contains basic elements that are necessary in order to build neural networks. Neural network classical models are already available (Multi-layer perceptron, Kohonen self-organizing maps, neural gas, growing neural gas, etc.). Platforms: Windows

Cognity is designed as an object-oriented neural network library for the Java programming language. The main goal of the library is to provide an easy-to-use, high level architecture for neural network computations along with reasonable performance. Platforms: Windows

RNNLIB is a recurrent neural network library for sequence learning problems. Applicable to most types of spatiotemporal data, it has proven particularly effective for speech and handwriting recognition. Platforms: Mac

This module works independently of the core search module.InstallationUnpack in your modules folder (usually /sites/all/modules/) and enable under Administer > Site Building > Modules. Key features "Fuzzy Search": - Mispellings and typos still provide relevant results. - External scoring factor... Platforms: Windows, Mac, *nix, PHP, BSD Solaris

This script is an ease of use subclass of dict - rather then one that uses a lot of dict features. If your request item is in the dictionary (with a key that hashes the same) then it acts as a more or less normal dictionary. If on the other hand you are looking for a string that is similar to a... Platforms: Windows, Mac, *nix, Python, BSD Solaris

This script uses the IAC (interactive-competition-and-activation) model to analyze a database. Scalyze a dils: - The example is taken from Parallel Distributed Processing, a classic text on neural networks. - The field values represent neurons. - The database rows represent excitory... Platforms: Windows, Mac, *nix, Python, BSD Solaris

The performance of the level set segmentation is subject to appropriate initialization and optimal configuration of controlling parameters, which require substantial manual intervention. A new fuzzy level set algorithm is proposed in this paper to facilitate medical image segmentation. It is able... Platforms: Matlab

Develop a Matlab program to demonstrate a neural network autoassociative memory. Show the importance of using the pseudoinverse in reducing cross correlation matrix errors. Show the performance of the autoassociative memory in noise. The results are contained in the Matlab file assoc_mem_demo.m Platforms: Matlab

A very simple program that trains a neural network with 9 images(3 rectangles, 3 triangles and 3 circles)and then simulates the neural network in way to recognize 3 others images(1 rectangles, 1 triangles and 1 circles). Platforms: Matlab

This set of programs correspond to demos, exercises, and implementations of algorithms described inAbdi H. (1994) Les Reseaux de Neurone (in French) andin (in English)Abdi, Valentin, Edelman (1999) Neural Networks. SageThese include:Linear auto and hetero associators, radial basis function... Platforms: Matlab

This package is created with the highly appreciated theoretical help and under the supervision of Prof. DSc. Ketty Peeva.Theoretical results and methods can be found in:1. B. De Baets, Analytical solution methods for fuzzy relational equations, in the series: Fundamentals of Fuzzy Sets, The... Platforms: Matlab

The archive includes genfis4.m that generates Mamdani- and Sugeno-type FIS using CART algorithm to extract fuzzy rule information from data set. It is based mostly on Fuzzy Logic Toolbox but it has required to modify Toolbox's fuzzy rule building principle. As a result some original m-files was... Platforms: Matlab

These files are obsolete. If you wish a more recent version download its from http://forja.rediris.es/frs/?group_id=644The methodology used for programing this utilities are described in the articles: * J.M. And?jar, A.J. Barrag?n, "A methodology to design stable nonlinear fuzzy control systems",... Platforms: Matlab

This function segments (clusters) an image into object classes, and estimates and corrects for slow varying illumination artifacts. Estimates and corrects for bias field in 3D MRI, streak artifacts in CT, and illumination artifacts in color photos.It's an implementation of the paper of M.N. Ahmed... Platforms: Matlab

The large classification margin is the most usual approach to achieve good generalization. The most known maximal margin algorithm is SVM, for which different kernels have been investigated. Unfortunately, in the context of some real world problems, such as on-the-fly object detection, the use of... Platforms: Matlab

This is a general purpose controller that I have built using the Fuzzy Logic Rules. You don't need to have any mathematical background in fuzzy logic to run this model.You don't need to have fuzzy logic toolbox to run it aswell.It contains both linear and a nonlinear examples. It also has a read... Platforms: Matlab

Schwarz, Shoelson & Amphlett, Retailers Of Fine MATLAB Cloth Since 1987, proudly announce another piece of visionary software: FPAT - A Fuzzy Pattern DetectorDid you ever listen to a toddler talk?Easily your brain finds words amongst the noisy babble...Did you ever think of faulty DNA?Easily... Platforms: Matlab

This little package contains a Parzen Neural Network classifier that can classify data between N classes in D dimensions. The classifier is really fast and simple to learn. The good classification performance can be obtained for a certain class of data distributions. Other classifiers must be... Platforms: Matlab

This function shall be used to evaluate the union or intersection between fuzzy sets or fuzzy relation under type2 category.For a complete understanding Please refer book by Dr. Jerry M. Mendel on:Uncertain Rule-Based Fuzzy Logic Systems:Introduction and New Directions Platforms: Matlab