Description: 用MATLAB实现蒙特卡骂法计算结构可靠度.
针对应用蒙特卡罗直接抽样法解决结构可靠度所遇到的困难，提出利用MATLAB的强大数值计算功能解决此类问题。
-Montecatini MATLAB scolded calculated structural reliability. Against direct Monte Carlo method for sampling Structural Reliability decision by the difficulties encountered, using MATLAB powerful numerical calculation function to solve such problems. Platform: |
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Author:左贤君 |
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Description: 蒙特卡罗（Monte Carlo）方法，又称随机抽样或统计试验方法，属于计算数学的一个分支，它是在本世纪四十年代中期为了适应当时原子能事业的发展而发展起来的。传统的经验方法由于不能逼近真实的物理过程，很难得到满意的结果，而蒙特卡罗方法由于能够真实地模拟实际物理过程，故解决问题与实际非常符合，可以得到很圆满的结果。-Monte Carlo (Monte Carlo) methods, also known as random sampling or statistical testing methods, belong to a branch of mathematical calculation, it is in the mid-forty years of this century in order to adapt to the development of atomic energy at the time and developed. The experience of traditional methods should not close as a result of real physical processes, it is difficult to get satisfactory results, while the Monte Carlo method because it can simulate the actual real physical process, so to solve the problem very much in line with the actual, can be a very successful outcome. Platform: |
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Author:wcy |
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Description: Hybrid Monte Carlo sampling.SAMPLES = HMC(F, X, OPTIONS, GRADF) uses a hybrid Monte Carlo
algorithm to sample from the distribution P ~ EXP(-F), where F is the
first argument to HMC. The Markov chain starts at the point X, and
the function GRADF is the gradient of the `energy function F. Platform: |
Size: 3072 |
Author:西晃云 |
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Description: Sequential Monte Carlo without Likelihoods
粒子滤波不用似然函数的情况下
本文摘要:Recent new methods in Bayesian simulation have provided ways of evaluating posterior distributions
in the presence of analytically or computationally intractable likelihood functions.
Despite representing a substantial methodological advance, existing methods based on rejection
sampling or Markov chain Monte Carlo can be highly inefficient, and accordingly
require far more iterations than may be practical to implement. Here we propose a sequential
Monte Carlo sampler that convincingly overcomes these inefficiencies. We demonstrate
its implementation through an epidemiological study of the transmission rate of tuberculosis.-Sequential Monte Carlo without Likelihoods Particle Filtering likelihood function do not have the circumstances of this article Abstract: Recent new methods in Bayesian simulation have provided ways of evaluating posterior distributionsin the presence of analytically or computationally intractable likelihood functions.Despite representing a substantial methodological advance, existing methods based on rejectionsampling or Markov chain Monte Carlo can be highly inefficient, and accordinglyrequire far more iterations than may be practical to implement. Here we propose a sequentialMonte Carlo sampler that convincingly overcomes these inefficiencies. We demonstrateits implementation through an epidemiological study of the transmission rate of tuberculosis . Platform: |
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Author:阳关 |
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Description: 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 Belief
Propagation, Mean-Field approximation, and 4 monte-carlo sampling methods
(Metropolis, Gibbs, Wolff, Swendsen-Wang).
Use "help inference" from Matlab to see all options for usage.
2. gbp_preprocess.m and gbp.m
These 2 interfaces split Generalized Belief Propagation into the pre-process
stage (gbp_preprocess.m) and the inference stage (gbp.m), so the user may use
only one of them, or changing some parameters in between.
Use "help gbp_preprocess" and "help gbp" from Matlab.
3. simulatedAnnealing.m
An interface to the simulated-annealing c-code. This code uses Metropolis
sampling method, the same one used for inference.
Use "help simulatedAnnealing" from Matlab. Platform: |
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Author:bevin |
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Description: The Hammersley and Halton point sets, two well known low discrepancy sequences, have been used for quasi-Monte Carlo integration in previous research. A deterministic formula generates a uniformly distributed and stochastic-looking sampling pattern, at low computational cost. The Halton point set is also useful for incremental sampling. In this paper, we discuss detailed implementation issues and our experience of choosing suitable bases of the point sets, not just on the 2D plane, but also on a spherical surface. The sampling scheme is also applied to ray tracing, with a significant improvement in error. Platform: |
Size: 25600 |
Author:tiantiancode |
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Description: 准蒙特卡罗采样方法的若干国外经典文献，适合该领域入门。-Quasi-Monte Carlo sampling method of a number of foreign classical literature, suitable for entry in the field. Platform: |
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Author:zhaolingling |
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Description: 课程设计中首先采用Ising model的思想建立一个二维的模型，然后利用重要性抽样和Monte Carlo方法及其思想模拟铁磁-顺磁相变过程。计算了顺磁物质的能量平均值Ev、热容Cv、磁化强度M及磁化率X的值，进而研究Ev、Cv、M、X与温度T的变化关系并绘制成Ev-T图、Cv-T图、M-T图、X-T图，得出顺磁物质的内能随着温度的升高先增大而后趋于稳定值；热容Cv、磁化率X随着温度的升高先增大后减小；磁化强度M在转变温度Tc处迅速减小为零，找出铁磁相变的转变温度Tc大约为2.35-First of all, curriculum design idea of the Ising model used to establish a two-dimensional model, the importance of sampling and then use Monte Carlo simulation methods and their idea of ferromagnetic- paramagnetic phase transition process. Paramagnetic material calculated average energy Ev, heat capacity Cv, magnetization M and susceptibility X value, and then study Ev, Cv, M, X and temperature changes in the relationship between T and plotted into Ev-T map, Cv- T diagram, MT map, XT maps drawn paramagnetic material can be increased as the temperature increased and then stabilized value heat capacity Cv, magnetic susceptibility X as the temperature increases after the first minus small magnetization M in the transition temperature Tc decreases rapidly to zero Department to identify ferromagnetic phase transition around the transition temperature Tc for 2.35 Platform: |
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Author:Ellison |
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Description: 粒子滤波(PF: Particle Filter)的思想基于蒙特卡洛方法(Monte Carlo methods)，它是利用粒子集来表示概率，可以用在任何形式的状态空间模型上。其核心思想是通过从后验概率中抽取的随机状态粒子来表达其分布，是一种顺序重要性采样法(Sequential Importance Sampling)。简单来说，粒子滤波法是指通过寻找一组在状态空间传播的随机样本对概率密度函数 进行近似，以样本均值代替积分运算，从而获得状态最小方差分布的过程。这里的样本即指粒子,当样本数量N→∝时可以逼近任何形式的概率密度分布。-Particle filter (PF: Particle Filter) ideas based on Monte Carlo methods (Monte Carlo methods), which is set to represent the probability of a particle, can be used in any form of state space model. The core idea is to extract from the posterior probability of the random state of particle to express the distribution is a sequential importance sampling method (Sequential Importance Sampling). In short, particle filtering method is by looking for a spread in state space probability density function of random samples to approximate to the sample mean instead of integral operators to gain distribution in the state minimum variance process. Here' s the sample i.e. particles, when the sample size N → α can approach any form of probability density distribution. Platform: |
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Author:fanlianxiang |
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Description: This program demonstrates an importance-sampling Monte Carlo integration to evaluate an integral. Platform: |
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Author:space21 |
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Description: 蒙特卡罗方法在由已知分布的随机抽样中的应用-Monte Carlo method of random sampling from the known distribution of the application Platform: |
Size: 380928 |
Author:xxit |
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Description: 基于蒙特卡罗算法的电力系统风险评估研究_李彦生。利用蒙特卡洛抽样和潮流计算方法计算电力系统可靠性-Based on the Monte Carlo algorithm for power system risk assessment studies _ Li Yansheng. Monte Carlo sampling and flow calculation method of the calculation of the power system reliability Platform: |
Size: 1072128 |
Author:fuying |
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Description: The Monte Carlo technique is a flexible method for simulating light propagation in tissue. The simulation is based on the random walks that photons make as they travel through tissue, which are chosen by statistically sampling the probability distributions for step size and angular deflection per scattering event. After propagating many photons, the net distribution of all the photon paths yields an accurate approximation to reality. Platform: |
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Author:jiff |
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Description: 序贯蒙特卡罗对误码率抽样，增强算法性能，程序源代码，实用易用-Sequential Monte Carlo sampling of the bit error rate and enhance the performance of the algorithm, source code, easy to use and practical Platform: |
Size: 2048 |
Author:单晓东 |
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Description: 基于蒙特卡洛抽样方法的介绍，有PPT，有详细解释，有程序算例(Based on the monte carlo sampling method is introduced, a PPT, has explained in detail, with application examples) Platform: |
Size: 712704 |
Author:青春的张扬俏
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Description: 这是从多元正态分布、均匀分布和经验分布中实现拉丁超立方体采样的采样实用程序。变量之间的相关性可以被描述出来。(This is sampling utility implementing Latin hypercube sampling from multivariate normal, uniform & empirical distribution. Correlation among variables can be sprecified) Platform: |
Size: 62464 |
Author:小文小文 |
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