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Code 41-60 of 60   Pages: Go to  << Prior  1  2  3  page  

Genetic Algorithms General Solver (GAGENES) is a C++ implementation of the genetic algorithm concept.

FGA (Fast Genetic Algorithm) is a simple yet powerful implementation of genetic algorithms. The library provides many variants of crossover and selection procedures, and a parallel version of the algorithm is included.

This is implementation of parallel genetic algorithm with "ring" insular topology. Algorithm provides a dynamic choice of genetic operators in the evolution of. The library supports the 26 genetic operators. This is cross-platform GA...

Quick and simple implementation of Gaussian mixture model (with same covariance shapes) based expectation-maximization algorithm.

An implementation of Butcher's Algorithm for determining the date of Easter for the Western church. Works for any date in the Gregorian calendar (1583 and onward). Returns a date object.

This is a simple python implementation of the XTEA block encryption algorithm ( For details please see docstrings in the code.

This is an implementation of the binary search algorithm in (almost) one line. Given a number 'n' and a list 'L', the function returns the index of the number on the list, or -1.

This is an implementation of Edmonds' blossom-contraction algorithm for maximum cardinality matching in general graphs. It's maybe a little long and complex for the recipe book, but I hope it will spare someone else the agony of implementing it...

This is an implementation of the Knuth-Morris-Pratt algorithm for finding copies of a given pattern as a contiguous subsequence of a larger text. Since KMP accesses the text only sequentially, it is natural to implement it in a way that allows...

An implementation of a round-robin algorithm for "fair" pairing of items from a list. The function produces a schedule of the pairings that can occur simultaneously.

Usage: [means,c]=KNMCluster(k,indata)

KNMCluster is an implementation of the K-means clustering algorithm. It takes inputs k and indata. k is the initial guess of the number of clusters.

indata is the aggregate data that you...

This project is a simple implementation of the Iterative Back-Projection (IBP)
algorithm for solving the Super-Resolution problem. It was first proposed
by Michal Irani in her 1991 paper "Improving resolution by image

This program is an implementation of nondominated sorting genetic algorithm II (NSGA-II) proposed by K. Deb. Capabilities:
1. R-NSGA-II: Reference-point-based NSGA-II.
2. Coding: real, integer.
3. GA operator: Intermediate...

Implementation of Levy et al's LSCM algorithm [1]. Also includes a basic Wavefront OBJ file format reader, and an implementation taking advantage of speed-ups available using JACKET from Accelereyes to perform some computations on an NVIDIA...

This is a Matlab implementation of a unique algorithm by J. D. Opdyke with very good properties for solving the Integer Composition problem of finding all permutations in the additive partitioning of integers. It also accepts lower and upper...

This is a parallel implementation of the Expectation Maximization algorithm for multidimensional Gaussian Mixture Models, designed to run on NVidia graphics cards supporting
CUDA. On my machine, it provides up to 170x performance increases...

This package contains a Matlab reference implementation of a novel algorithm to estimate the direct-to-reverberant energy ratio (DRR) blindly from a dual-channel reverberant speech signal.

Within the Matlab script 'DRR_est_example.m', a...

This is an implementation of exact geodesic algorithm for triangular mesh (first described by Mitchell, Mount and Papadimitriou in 1987) with some minor improvements, extensions and simplifications. The algorithm has O(n^2 log n) worst-case time...

Implementation of the algorithm proposed in the paper:

Morhac, M., 1991 - A Fast Algorithm of Nonlinear Volterra Filtering

Basically, the output of each n-homogeneous subsystem is decomposed into a summation of convolutions....

Mex implementation of EM algorithm for multivariate Gaussian mixture. Multiple data/initial parameters are allowed by ND slices definition

em_mvgm : Expectation-Maximization algorithm for Multivariate Gaussian Mixtures