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一个声讯小姐的隐秘日记
- 欲望与理性的挣扎!不断地自欺和伪装,不断地付出与失去她们为了在繁华的都市生存并长期居留,日夜出卖自己甜美柔媚的嗓音,甚至不惜肉体,可最后除了身心疲惫,伤痕累累外,沦为被整个社会鄙视的“罂粟花”…… - Desire and rational struggling! Unceasingly deceives self with the camouflage, unceasingly pays with loses them for in
模拟退火例子1
- 模拟退火算法来源于固体退火原理,将固体加温至充分高,再让其徐徐冷却,加温时,固体内部粒子随温升变为无序状,内能增大,而徐徐冷却时粒子渐趋有序,在每个温度都达到平衡态,最后在常温时达到基态,内能减为最小。根据Metropolis准则,粒子在温度T时趋于平衡的概率为e-ΔE/(kT),其中E为温度T时的内能,ΔE为其改变量,k为Boltzmann常数。用固体退火模拟组合优化问题,将内能E模拟为目标函数值f,温度T演化成控制参数t,即得到解组
模拟退火例子2
- 模拟退火算法来源于固体退火原理,将固体加温至充分高,再让其徐徐冷却,加温时,固体内部粒子随温升变为无序状,内能增大,而徐徐冷却时粒子渐趋有序,在每个温度都达到平衡态,最后在常温时达到基态,内能减为最小。根据Metropolis准则,粒子在温度T时趋于平衡的概率为e-ΔE/(kT),其中E为温度T时的内能,ΔE为其改变量,k为Boltzmann常数。用固体退火模拟组合优化问题,将内能E模拟为目标函数值f,温度T演化成控制参数t,即得到解组
模拟退火例子3
- 模拟退火算法来源于固体退火原理,将固体加温至充分高,再让其徐徐冷却,加温时,固体内部粒子随温升变为无序状,内能增大,而徐徐冷却时粒子渐趋有序,在每个温度都达到平衡态,最后在常温时达到基态,内能减为最小。根据Metropolis准则,粒子在温度T时趋于平衡的概率为e-ΔE/(kT),其中E为温度T时的内能,ΔE为其改变量,k为Boltzmann常数。用固体退火模拟组合优化问题,将内能E模拟为目标函数值f,温度T演化成控制参数t,即得到解组
c_inference_ver2.2
- The package includes 3 Matlab-interfaces to the c-code: 1. inference.m An interface to the full inference package, includes several methods for approximate inference: Loopy Belief Propagation, Generalized Beli
模拟退火例子1
- 模拟退火算法来源于固体退火原理,将固体加温至充分高,再让其徐徐冷却,加温时,固体内部粒子随温升变为无序状,内能增大,而徐徐冷却时粒子渐趋有序,在每个温度都达到平衡态,最后在常温时达到基态,内能减为最小。根据Metropolis准则,粒子在温度T时趋于平衡的概率为e-ΔE/(kT),其中E为温度T时的内能,ΔE为其改变量,k为Boltzmann常数。用固体退火模拟组合优化问题,将内能E模拟为目标函数值f,温度T演化成控制参数t,即得到解组
模拟退火例子2
- 模拟退火算法来源于固体退火原理,将固体加温至充分高,再让其徐徐冷却,加温时,固体内部粒子随温升变为无序状,内能增大,而徐徐冷却时粒子渐趋有序,在每个温度都达到平衡态,最后在常温时达到基态,内能减为最小。根据Metropolis准则,粒子在温度T时趋于平衡的概率为e-ΔE/(kT),其中E为温度T时的内能,ΔE为其改变量,k为Boltzmann常数。用固体退火模拟组合优化问题,将内能E模拟为目标函数值f,温度T演化成控制参数t,即得到解组
c_inference_ver2.2
- The package includes 3 Matlab-interfaces to the c-code: 1. inference.m An interface to the full inference package, includes several methods for approximate inference: Loopy Belief Propagation, Generalized Beli
gibbs_metropol_sampler
- this r code for Gibbs sampler and Metropolis sampler which are two variants of markov chain monte carlo simulators.-this is r code for Gibbs sampler and Metropolis sampler which are two variants of markov chain monte car
TestMarkovIsingbyMetropolis
- MRF example, Ising by Metropolis
mh
- metropolis-Hastings samplermetropolis-Hastings抽样的matlab实现-metropolis-Hastings samplermetropolis-Hastings in matlab
mallows_MH
- Metropolis sampler for Mallows model samples orderings from a distribution over orderings
metropolis
- Use Metropolis procedure to sample from Cauchy density
Adaptive-Mixture-Modelling-Metropolis-Methods
- Adaptive Mixture Modelling Metropolis Methods using matlab
metropolis
- matlab code for metropolis algorithm
Metropolis-Hastings
- 使用metropolis-hastings抽样方法,产生平稳马尔科夫链,R语言实现-Using sampling methods metropolis-hastings, produce smooth Markov chain, R language
metropolis_hastings
- 本文件包含Metropolis算法对函数进行抽样;显示生成样本的相关图和直方图. 其中文件:metropolis_hastings.m该文件包含4个示例,用于通过Metropolis-Hastings算法对复杂函数进行抽样,显示生成样本的相关图和直方图。metropolis_hastings2.m 包含一个例子,用于通过Metropolis-Hastings算法对双变量高斯PDF进行采样,显示生成样本的相关图和直方图,以及其轮廓和边缘
Metropolis-Hasting Random Walk
- Metropolis Hastings code
IsingModelAndMetropolisAlgorithm
- Ising模型的蒙特卡罗模拟.模拟能量及磁矩随温度变化(Ising Model And Metropolis Algorithm. Copyright 2017 The MathWorks, Inc.)
metropolis-hastings
- 一种用于对各类概率密度函数进行样本采样的Metropolis-Hastings算法(a Metropolis-Hastings algorithm for sampling from various probability density functions)