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 Euclidean Distance Algorithm Java 

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This program tests an input matrix to see if it is a Euclidean distance matrix to within a user-specified tolerance. If not, it reports why and returns the closest EDM in the sense of Schoenberg.

This function computes the minimum euclidean distance between two polygons P1 & P2.

- for vertex-vertex case

QT clustering algorithm as described in:

Heyer, L. J., Kruglyak, S., Yooseph, S. (1999). Exploring expression data: Identification and analysis of coexpressed genes. Genome Research 9, 1106d-deOCt1115.

% Find pair-wise SQUARE EUCLIDEAN distance
% or 'Weighted square euclidean' distance
% between each point in A and B
% For 2 vector a, b
% Euclidean distance= d = sum((a-b).^2)
% Weighted version = d =...

A test suite and benchmark for exact Euclidean distance transform algorithmsused in Image Processing and computational geometry. It evaluates theexactness and speed of algorithms for a large number of testcases. Results can be visualized in Scilab.

Post Miner helps your audience discovering relevant content on your blog without searching. The plugin uses Euclidean distance and collective intelligence* (CI will be available from version 1.1.x) to provide a good match and better user...

The purpose of the speech is communication. The area of speech processing is just developing, and shows the tremendous potentialities for widespread use in the future.

In this project we have processed the speech signal with the help of...

Iris data set clustering using partitional algorithm. Concepts like loading text document and plotting of 4 Dimensional data with the fourth dimension as the intensity of colour of the plot. I used K means algorithm to update the centres from...

DIJKSTRA Calculate Minimum Costs and Paths using Dijkstra's Algorithm

[AorV] Either A or V where
A is a NxN adjacency matrix, where A(I,J) is nonzero if and only if an edge connects point I to point J

SIMPLETRACKER a simple particle tracking algorithm that can deal with gaps

*Tracking* , or particle linking, consist in re-building the trajectories
of one or several particles as they move along time. Their position is

[L, C, D] = FKMEANS(X, k) partitions the vectors in the n-by-p matrix X
into k (or, rarely, fewer) clusters by applying the well known batch
K-means algorithm. Rows of X correspond to points, columns correspond to
variables. The...

A Zipped file has eight files which are related to Demo2D.m and Demo3D.m. The Demo2D removes the points in 2D-space and also find out non-overlapped points in their strongest magnitude order. The Demo3D does it in 3D-space. The core file is...

A given polynomial p(x) is transformed into a rational function r(x). The poles and residues of the derived rational function are found to be equivalent to the roots and multiplicities of the original polynomial.
p(x) = Given polynomial

Cluster validation is an important and necessary step in cluster analysis. This visual cluster validation tool CVAP based on GUI provides important tools and convenient analysis environment for validity evaluation of clustering solutions,...

slmetric_pw.h is an m-function to compute metrics between two sets of vectors in pairwise way.

Main Features:

-- It supports about 20 metric types, including Euclidean distance (L2), Normalized Correlation, City-Block...

Usage: createColorHistograms(im_str)
im_str can be an image file location or a three-dimensional array

There seem to be two confounds in plotting color histograms. One is the obvious one of showing a three-dimensional distribution...

The package contains a set of C functions and preprocessor macros to simplify writing MEX source files. The routines help check input and output argument count, argument type, dimension and structure in a MEX file. See "common.c" in the...

This script can be used alongside MATLAB's native function lab2double (CIELAB to RGB conversion).

CIELAB is a nonlinear transformation of RGB where the Euclidean distance between two colors is equal to their perceptual distances (for...

Compute the distance map to a set of points using the fast marching algorithm.
Solves the 2-D eikonal PDE.

Vincenty published an algorithm for calculating the distance between two latitudes and longitudes and another to find the destination latitude and longitude, given the start coordinate, bearing and distance