Fast mutual information of two images or signals

Optimized function for mutual information of two images or signals

information is obtained on the intersection between the supports of partial histograms.Example (in mi_test.m):disp('Test: Mutual information between two images')load mri A=D(:,:,8); B=D(:,:,9);mi(A,B)disp('Test

Mutual Average Information

Calculates the Mutual Average Information of a time series

Calculates the Mutual Average Information of a time series for some time lag.

Average mutual information

Average mutual information

Very fast implementation of average mutual information. Usage: [v,lag]=ami(x,y,lag) Calculates the mutual average information of x and y with a possible lag. v is the average mutual information

a function with the simplest form to calculate the mutual information

Here is a function with the simplest form to calculate the mutual information between two images.

MI is a good approach to align two images from different sensor. Here is a function with the simplest form to calculate the mutual information between two images.the function f=cal_mi(I1,I2) is in

The Adjusted Mutual Information

The Adjusted Mutual Information for clustering comparison

This program calculates the adjusted mutual information for comparing clusterings. It includes:- The mutual information/adjusted mutual information- The Rand index and some other indices(see

GCMI: Gaussian copula mutual information

Calculating mutual information and other quantities using a parametric Gaussian copula.

Functions for calculating mutual information and other information theoretic quantities using a parametric Gaussian copula.This provides a robust rank based statistic that can handle multidimensional

Mutual Information -2 variablle

Estimate Mutual Information with kernel density function

The function will estimate Estimate Mutual Information with kernel density function

Kernel estimate for (Conditional) Mutual Information

Estimates Mutual Information and Conditional Mutual Information between continuous random variables

Mutual information I(X,Y) measures the degree of dependence (in terms of probability theory) between two random variables X and Y. Is is non-negative and equal to zero when X and Y are mutually

Mutual Information In probability theory and information theory

Code for marginally and conditional mutual information in probability and information theory

The definition of mutual information could resort to wiki: http://en.wikipedia.org/wiki/Mutual_informationFor marginal mutual information, we say it is : I(A,B)=sum sum P(A,B) log[P(A,B)/P(A)P(B)]For

Mutual Information computation

A self-contained package for computing mutual information, joint/conditional probability, entropy

A self-contained, cross-platform, package for computing mutual information, joint/conditional probability, entropy, and more. This package has also been used for general machine learning and data

Fuzzy Entropy and Mutual Information

An implementation of the theory of fuzzy entropy and fuzzy mutual information.

Nowadays there are heaps of articles on the theory of fuzzy entropy and fuzzy mutual information. However, there is a clear significant lack for a Matlab implementation of these concepts. Based on

Feature Mutual Information (FMI) metric for non-reference image fusion

FMI is a non-reference image fusion metric based on mutual information of image features.

FMI calculates the Feature Mutual Information (FMI), the non-reference performance metric for fusion algorithms, proposed in: M.B.A. Haghighat, A. Aghagolzadeh, H. Seyedarabi, "A Non-Reference

mutual_information_images(im1, im2)

this software finds mutual information between two images

this software takes two images and return their mutual information. generally, If these two image do not belong to a same scene, their MI is minimum.

Feature Selection Using BBPSO with Mutual Information

a algorithm of feature selection, called BBPSO-based feature selection with mutual information (MIBBPSO)

Particle Swarm Optimization with Mutual Information ", which have been submitted to the journal Pattern Recognition. In this toolbox, the main function is named as “main”.

MUTUALINFO

Multiple mutual information (interaction information)

MUTUALINFO(X,P,idx) returns the multiple mutual information (interaction information) for the joint distribution provided by object matrix X and probability vector P. Each row of MxN matrix X is an

mrTools

mrTools - matlab based tools for fMRI

Very fast Mutual Information betweentwo images.

This function computes the mutual information between two quantized images.

function M = MI_GG(X,Y)Computes the mutual information between two quantized images: X and Y.For Citation: M. Ceccarelli, M. di Bisceglie, C. Galdi, G. Giangregorio, S.L. Ullo, “Image Registration

Normalized Mutual Information

Fully vectorized implementation NMI. NMI is often used for evaluating clustering results.

Normalized mutual information is often used for evaluating clustering results, information retrieval, feature selection etc. This is a optimized implementation of the function which has no for

Information Theoretic Feature Selection

Implementation for state-of-the-art mutual information based feature selection methods

)- Quadratic programming feature selection (QPFS)- Mutual information quotient (MIQ)- Maximum relevance minimum total redundancy (MRMTR) or extended MRMR (EMRMR)- Spectral relaxation global Conditional Mutual

Measures of Analysis of Time Series toolkit (MATS)

MATS computes many measures of scalar time series analysis on many time series in one go.

mRMR Feature Selection (using mutual information computation)

This is a cross-platform version of mimimum-redundancy maximum-relevancy feature selection

top-ranking method has been demonstrated on a number of data sets in recent publications. This version uses mutual information as a proxy for computing relevance and redundancy among variables (features). Other

Feature Selection Based on Interaction Information

Self-contained package for feature selection based on mutual information/interaction information.

, mutual information and interaction information are included and are usable by themselves. See demo_feature_select.m for examples.

Toolbox signal

Signal processing related functions.

Image Registration (2D) using Mutual Information (Optimization toolbox needed)

This is an updated automatic image registration using mutual information for users of IP toolbox.

[2D Mutual Information Matching using Optimization toolbox]This is an updated automatic image registration using mutual information for users of IP toolbox coded by Kateryna Artyushkova from The

Mutual information

Mutual Information measures using kNN for both continuous and categorical (discrete) variables

Mutual Information (Matlab code)Calculate the mutual information using a nearest-neighbours method for both the continuousversus continuous variable (Kraskov et al. 2004) and for the continious

Automatic Image Registration using (Normalized) Mutual Information for users of IP toolbox

Rigid (translation and rotation) automatic registration of images using normalized mutual informati

Functions for aligning images by rotation and translation: image_registr_MI.m MI2 - calculating Mutual informationjoint_h - calculating Joint histogramMutual information is calculated using joint

Mutual Information

Calculates the mutual information between two discrete variables (or a group and a single variable).

MutualInformation: returns mutual information (in bits) of discrete variables 'X' and 'Y' I = MutualInformation(X,Y); I = calculated mutual information (in bits) X = variable(s) to be analyzed

Windowed mutual information (migram)

Computes a windowed mutual information

Calculate windowed mutual information between two signals up to a pre-defined lag. The estimation of the (joint) probabilities is optimized, hence, entire computation is very fast.

Image mutual information

Fast mutual information calculation for images with consistent results to MATLAB built-in entropy() function.

MATLAB mutualInfo functionFast MATLAB function to calculate the mutual information of two images. Designed specifically for speed and to emulate functionality of MATLAB native entropy function. For

ent(varargin)

Built for 'highest possible' speed. Can handle any number of dimensions, given sufficient memory.

Information Theory Toolbox

Functions for Information theory, such as entropy, mutual information, KL divergence, etc

information6)Normalized mutual information7)Normalized variation informationThis package is now a part of the PRML toolbox (http://www.mathworks.com/matlabcentral/fileexchange/55826-pattern-recognition-and-machine

PECUZAL embedding algorithm for Matlab

This is the PECUZAL implementation for Matlab. An automated approach for attractor reconstruction of uni- and multivariate datasets.

`pecuzal-embedding.mltbx`. For further information also see the documentation (`Examples`).

mutual coherence of a matrix

This function computes the mutual coherence of a matrix

This function computes the mutual coherence of a matrix.Input: a real or complex matrix with more than one column.Ouput: the mutual coherence.

Normalized Mutual Information (NMI) for Cluster Analysis

A MATLAB implementation for calculating Normalized Mutual Information (NMI) to measure the similarity between two clusterings.

This MATLAB function provides a straightforward method to calculate the Normalized Mutual Information (NMI) between two sets of cluster assignments. NMI is a valuable measure in clustering as it can

ami and correlation

Computes and plots average mutual information and correlation for time series data.

AMI computes and plots average mutual information (ami) and correlation of univariate or bivariate time series for different values of time lag.USAGE: [amis corrs] = ami(xy,nBins,nLags)INPUT: xy

Permutation Conditional Mutual Information (PCMI)

Estimation of a directionality index between two time series

[Dxy,Ixy,Iyx] = CMI_PE_tau(X,Y,ord,t,Tau)PCMI: a novel methodology based on permutation analysis and conditional mutual information for estimation of a directionality index between two time series

image_MI.m

Image copy move detection using mutual information

The code try to detect if there any copy move attempt has been done , the sample image is forged with copy move technique . The algorithm detects tampering using regional mutual information .

Submodular Function Optimization

This toolbox provides functions for maximizing and minimizing submodular set functions.

detection / facility location* sfo_fn_infogain: Information gain about gaussian random variables* sfo_fn_entropy: Entropy of Gaussian random variables* sfo_fn_mi: Gaussian mutual information* sfo_fn_varred

Partial Rank Correlation Coefficients

Function for calculating the partial rank correlation coefficient for a variable number of model parameters

This function serves as a means of calculating the partial rank correlation coefficients (PRCCs) of a set of equally sized (n,1) input arrays, p1, p2,... where the last input is the response of the

pde1dM

pde1dm is a 1D PDE solver that supports high order interpolation functions, coupled ODE and is compatible with pdepe input syntax

# pde1dm1D Partial Differential Equation Solver for MATLAB and Octave`pde1dm` solves systems of partial differential equations (PDE) in a singlespatial variable and time. The input is mostly

Partial Fast Fourier Transform

Fast computation of part of an FFT using fractional fourier transform

Channel capacity using Arimoto-Blahut Algorithm

To find Channel capacity by maximizing mutual information w.r.t source symbol probability matrix Pc.

To find channel capacity one must maximize the mutual information with respect to the discrete set of probabilities of the source symbols 'c' , and for a given transition probability matrix.An

GlobalMIT toolbox

Learning Globally Optimal Dynamic Bayesian Network with the Mutual Information Test (MIT) Criterion

present GlobalMIT, a toolbox for learning the globally optimal DBN structure using a recently introduced information theoretic based scoring metric named mutual information test (MIT). Under MIT, learning

Automatic Image Registration

Using mutual information for users with no access to IP toolbox.

Functions for aligning images by rotation and translation: im_reg_MI.m MI2 - calculating Mutual informationjoint_h - calculating Joint histogramMutual information is calculated using joint histogram

Example Turbo Coding with free distance, EXIT code, and Presentation

Suitable for self-study or presenting to others, run full Turbo code simulations.

Entropy triangle

A set of visual entropy-based tools to assess the performance of multiclass classifiers.

mutual information, variation of information of entropy decrement. We have also added a script (compareETs) to visualize your own ETs and to print the NIT and EMA vs. other measures in latex-ready format

B-spline Grid, Image and Point based Registration

B-spline registration of two 2D / 3D images or corrsp. points, affine and with smooth b-spline grid.

. Also including, localized normalized mutual information as registration error, allowing the images or volumes to be of a different type/modality for instance a MRI T1 and T2 patient scan.How it works:A

MRI Partial Fourier reconstruction with POCS

Fast and robust reconstruction of Cartesian partial Fourier MRI data with POCS

POCS (Projection Onto Convex Sets) is often used to reconstruct partial Fourier MRI data.This implementation works with 2D or 3D data on a Cartesian grid. It is optimized for speed and automatically

Information Bottleneck iterative algorithm

The MATLAB implementation of the "Information Bottleneck Iterative Algorithm

The MATLAB implementation of the "Information Bottleneck Iterative Algorithm" presented in "The Information Bottleneck Method, Naftali Tishby, Fernando C. Pereira and William Bialek". Including a

Partial Least-Squares and Discriminant Analysis

A tutorial and tool using PLS for discriminant analysis.

Patial Least-Squares (PLS) is a widely used technique in various areas. This package provides a function to perform the PLS regression using the Nonlinear Iterative Partial Least-Squares (NIPALS

Carson's integral

Exact computation of the earth return impedance of overhead conductors above homogeneous earth.

evaluate to a closed-form expression, a scrutiny of Carson's historical (1926) paper reveals that such an expression exists and was actually presented therein. Functions Carson_Self and Carson_Mutual compute

Code for the Extreme learning machine and adaptive sparse representation algorithm (EA-SRC)

Code for the Extreme learning machine and adaptive sparse representation algorithm (EA-SRC)

EXIT chart computation

Matlab class implementing several methods for the computation of EXIT charts.

EXtrinsic Information Transfer (EXIT) charts are useful for characterizing the convergence properties and the performance of turbo receivers. Turbo receivers are generally constructed from two or

PARTPERM -- Partial random permutation of a vector

Partial random permutation of a vector.

Read information from Zeiss CZI image file.

This function returns various information on a Zeiss CZI image file.

Czifinfo read information from a Zeiss CZI image file.

Get Keyboard Information

Keyboard information, mouse events

This simple example assists you to understand how to get the keyboard information as well as mouse events.

System Information Class for Windows

This class will query the current system information in MATLAB. Works with R2009a and up.

can do it inside MATLAB. But with the recent and excellent .Net support, this is actually quite easy and straightforward.This class, wrapping all the basic information regarding to you Windows machine

Vectorized Relaxation Algorithm For Solving Linear Partial Differential Equations

Utilizes a vectorized relaxation algorithm to solve linear partial differential equations.

This program utilizes a vectorized relaxation algorithm in order to solve linear partial differential equations. Please submit any suggestions you have for improving the program (I would eventually

Density-ratio based clustering

Discovering clusters with varying densities

Coding of Analog Signals

Set of scripts for source and channel coding in telecommunications.

Lempel-Ziv'78 Coding. Calculation of Mutual Information and Channel Capacity (Non-symmetric and Symmetric Channel).