Search Results for "clustering algorithm matlab" - Page 6
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Showing 182 open source projects for "clustering algorithm matlab"
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Open Genetic Algorithm Toolbox
This is a MATLAB toolbox to run a GA on any problem you want to model.
This is a toolbox to run a GA on any problem you want to model. You can use one of the sample problems as reference to model your own problem with a few simple functions. You can collaborate by defining new example problems or new functions for GA, such as scaling, selection or adaptation methods. In that case, you should then include your credits in the file, upload it to matlab central and contact the author. Suggestions are also welcome but naturally I won't be able to attend... -
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ACADO Toolkit
Toolkit for Automatic Control and Dynamic Optimization
ACADO Toolkit is a software environment and algorithm collection for automatic control and dynamic optimization. It provides a general framework for using a great variety of algorithms for direct optimal control, including model predictive control, state and parameter estimation and robust optimization. ACADO Toolkit is implemented as self-contained C++ code and comes along with user-friendly MATLAB interface. The object-oriented design allows for convenient coupling of existing optimization... -
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NeuralGas
Self-organized learning
A collection of algorithms based on the topology preserving Neural Gas algorithm for density estimation/quantization/clustering/self-organized learning. I moved this project to GitHub: https://github.com/sergioroa/neuralgas -
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ISAD
Individual Synaptic Activity Detection (ISAD)
... of Spontaneous Vesicle Release at Individual Synapses Using Multiple Wavelets in a CWT-Based Algorithm. Med Image Comput Comput Assist Interv (MICCAI). 2012;15(Pt 1):165-72 ISAD is written in MATLAB and comes with a graphical user interface. -
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Stanford Machine Learning Course
machine learning course programming exercise
The Stanford Machine Learning Course Exercises repository contains programming assignments from the well-known Stanford Machine Learning online course. It includes implementations of a variety of fundamental algorithms using Python and MATLAB/Octave. The repository covers a broad set of topics such as linear regression, logistic regression, neural networks, clustering, support vector machines, and recommender systems. Each folder corresponds to a specific algorithm or concept, making it easy... -
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EToS (Efficient Technology of Spike sorting; Extracellular recording To Spike trains) is an open-source system for spike sorting. EToS contains the programs of spike detection, feature extraction and clustering.
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Rand Tree
Random Tree Generator for MatLab
RandTree is a MatLab based tree simulator program where the algorithm is based on Honda's model. We have used probabilistic generation of branches in order to simulate visually realistic tree structures. This program is designed to generate branching structures with bifurcation branching pattern (sympodial branching). By changing the probabilities and branching angles, you can generate different shapes of trees. -
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CvHMM
Discrete Hidden Markov Models based on OpenCV
This project (CvHMM) is an implementation of discrete Hidden Markov Models (HMM) based on OpenCV. It is simple to understand and simple to use. The Zip file contains one header for the implementation and one main.cpp file for a demonstration of how it works. Hope it becomes useful for your projects. -
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Galaxy-based Search Algorithm
Continuous Optimization by Galaxy-based Search Algorithm (the GbSA)
In this Project, it is attempted to implement the software for the Galaxy-based Search Algorithm (the GbSA). The GbSA is a continuous optimization algorithm inspired from nature. It tries to mimic the spiral movement of spiral galaxies along with a chaotic process to search the solution space for a given continuous optimization problem. For this purpose, a local search is also employed for fine-tuning of the obtained solution. For the first implementation, the GbSA is developed for MATLAB... -
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This is a MATLAB implementation of inverse compositional Active Appearance Models (AAMs), as described in the "Active Appearance Models Revisited" paper by Iain Matthews and Simon Baker.
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Note: This project is no longer maintained. An updated pure Python and experimental MatLab versions are located at https://github.com/robb-brown/GFT. The Fast S-Transform package implements a novel algorithm that solves the S-Transform with O(NlogN) computational complexity. This Fast S-Transform algorithm is fully invertible, and requires only O(N) storage space.
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EGA
A novel and effictive GA algorithm to solve optimization problem
Classical genetic algorithm suffers heavy pressure of fitness evaluation for time-consuming optimization problems. To address this problem, we present an efficient genetic algorithm by the combination with clustering methods. The high efficiency of the proposed method results from the fitness estimation and the schema discovery of partial individuals in current population and. Specifically, the clustering method used in this paper is affinity propagation. The numerical experiments... -
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BLIMToolbox
A set of tools for processing Argus images of the nearshore zone.
BLIM Toolbox is a collection of tools for the extraction and analysis of visual features in Argus images of the nearshore zone. The toolbox provides an implementation of the BarLine Intensity Mapper (BLIM) algorithm, which extracts high-intensity bands from Argus images. Also, several analysis and export functions are included in this toolbox, such as timestack plots and movies. The main incentive for the development of this toolbox was reducing the amount of time and effort a user spends... -
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K-link
Read clustering algorithm which identifies and removes chimeric reads
This project was developed for ESTs. However, there is no reason it cannot be extended for use on amplicon sequences from 454. It is used in conjunction with WCDest clustering software. -
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Gepoclu - Gene Positional Clustering is a suite of Matlab functions for performing positional clustering on genes with optional use of expression data such as what can be obtained from Microarray, EST and qRT-PCR, and PCR.
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Code of the algorithm described in the JMLR paper "Training a Laplacian Support Vector Machine in the Primal" (Authors: Stefano Melacci, Mikhail Belkin). You can download the MATLAB implementation from: http://www.dii.unisi.it/~melacci/lapsvmp/
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PocketAnalyzerPCA combines a geometric algorithm for detecting pockets in proteins with Principal Component Analysis and clustering. This enables visualization and analysis of pocket conformational distributions of large sets of protein structures.
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Leark is a Data Mining library developed in C#.NET. It contains several methods for ranking web documents described with a set of normalized features, and a feature selection algorithm. The methods are based on perceptron and clustering.
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This is a fast C implementation of Arturo Camacho's SWIPE' pitch extraction algorithm. See the project homepage for more about the advantages of the SWIPE' algorithm. swipe-1.0.tar.gz contains the current source, which should compile quite neatly.
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Complex Systems is a toolbox for SCILAB software. This toolbox measures some parameters for graphs representing complex systems: degree distribution, average neighboring degree, average clustering, and shell index (from k-core decomposition).
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A MATLAB spectral clustering package to handle large data sets (200,000 RCV1 data) on a 4GB memory general machine. We implement various ways of approximating the dense similarity matrix, including nearest neighbors and the Nystrom method.
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This project applies an interpretation of a k-NN algorithm to a library of GPS commuter data for speed prediction. The overall goal is to lay the foundation for a power management protocol for use in electric vehicles with hybrid energy storage.
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A tool to automate (i) software/algorithm benchmarking varying a set of control parameters, (ii) manage and summarize the results using plots and tables. The software works with any standalone command line based software or MATLAB.
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BorderFlow implements a general-purpose graph clustering algorithm. It maximizes the inner to outer flow ratio from the border of each cluster to the rest of the graph.
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