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UniformDistributionPURPOSE
Uniform probability on a continuous space.
SYNOPSIS
function [p v]=UniformDistribution(CS)
DESCRIPTION
Uniform probability on a continuous space. Generates a uniform distribution on the bounds defining the given continuous space. Right now, the output is a Gaussian mixture with a single component with a spherical covariance defined given the bounds of the space in each dimension. Parameters: CS: The continuous space where to define the probability distribution. Outputs: p: The Gaussian mixture. v: Value for the distribution in the continuous space. This is lower as the space gets larger. In principle this is the same value as that returned by UniformProbability but it could be slightly different since the returned distribution is only an approximation of the uniform distribution and not the real one. See also @CSpace/UniformProbability. CROSS-REFERENCE INFORMATION
This function calls:
SOURCE CODE
0001 function [p v]=UniformDistribution(CS) 0002 % Uniform probability on a continuous space. 0003 % 0004 % Generates a uniform distribution on the bounds defining the given 0005 % continuous space. 0006 % Right now, the output is a Gaussian mixture with a single component 0007 % with a spherical covariance defined given the bounds of the space in 0008 % each dimension. 0009 % 0010 % Parameters: 0011 % CS: The continuous space where to define the probability 0012 % distribution. 0013 % Outputs: 0014 % p: The Gaussian mixture. 0015 % v: Value for the distribution in the continuous space. This is lower 0016 % as the space gets larger. In principle this is the same value as 0017 % that returned by UniformProbability but it could be slightly 0018 % different since the returned distribution is only an approximation 0019 % of the uniform distribution and not the real one. 0020 % 0021 % See also @CSpace/UniformProbability. 0022 0023 d=CS.max-CS.min; 0024 md=max(d); 0025 c=CS.min+d/2; 0026 g1=Gaussian(c,ones(CS.dim)*200*md); 0027 p=GMixture(1,{g1}); 0028 v=Value(g1,CS.min); 0029 |