搜索资源列表
inference.tar
- gibbs,beyesian network,intelligent inference, Markov, BeliefPropagation. It is a very good surce code for intelligent reasoning research-gibbs, beyesian network, intelligent inference, Markov, BeliefPropagation. It is a very good surce code for int
FluidPipelineSimulinkModels
- These Simulink blocks contain transfer functions that model the pressure and flow transients for axisymmetric 2D viscous flow of a compressible fluid in a straight rigid circular cross section pipelines. Three models are available: (1) pressure
sparfilt
- 优点:1.对于信噪比高的信号滤波效果好; % 2.对于边沿的保护强过阈值滤波,不会产生阈值滤波情况下的过于平滑与Gibbs现象。 %缺点:1.由于对边沿信号没做任何处理,所以边沿可能会有脉冲噪声保留下来; % 2.计算相关系数中,如果计算出来的小波系数点位置偏差大,则相关系数计算受影响; % 3.需要迭代运算,迭代的噪声能量阈值选取很重要,这里以开始段无信号处估计噪声; % 4.需要迭代运算,所以运算量比阈值法大; % 5.受分解层次影响,在大尺度上小波系数点位置偏差更大
cycle_spinning
- 内含两个程序:1.平移变换平移法(cycle_spinning)消除gibbs(吉布斯)效应 2.MATLAB中测试程序运行时间的函数.m
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 Belief Propagation, Mean-Field
wavelet_matlab_code.rar
- 2代小波示意程序 2维小波变换经典程序 Daubechies小波基的构造 采用多孔trous算法(undecimated wavelet transform)实现小波变换 平移变换平移法(cycle_spinning)消除gibbs效应 提升法97经典程序 消失矩作用的程序 小波插值与小波构造 小波滤波器构造和消噪程序 小波谱分析mallat算法经典程序,2 Generation Wavelet indicated procedures classic 2-D wavelet
JAGS-2.2.0.tar
- 基于吉布斯采样的算法源码,对要从事算法研究的人很有帮助。-Gibbs sampling algorithm based on source code, for people who want to be helpful in the algorithm.
Lattice_Filters
- 一个信号处理的matlab代码关于Gibbs现象-A signal processing matlab code On the Gibbs phenomenon
OpenBUGS
- 这是国外研究Gibbs采样和Bayesian推理的研究人员写的工具包软件,最新版本为V1.4.3。很适合研究机器学习及其贝叶斯推理的科研人员使用。-The BUGS (Bayesian inference Using Gibbs Sampling) project is concerned with flexible software for the Bayesian analysis of complex statistical models using Markov chain Monte
main3
- An example that illustrates the importance of shift-invariance is image denoising by thresholding where the lack of shift-invariance causes pseudo-Gibbs phenomena around singularities.In addition to shift-invariance, it has been recognized that a
Gibbs_Phenomena_CFST
- 离散傅里叶变换中的吉布斯效应。这里分别讨论了CFST和CFT两种情况,程序可以直接调用-Discrete Fourier transform of the Gibbs effect. Are discussed here, two cases CFST and CFT, the program can directly call
BVAR_Gibbs
- 贝叶斯分析,比较复杂的自回归分析。VAR模型,注意比AR要先进的多!-Bayesian estimation, prediction and impulse response analysis in VAR models using the Gibbs sampler.
2dgaussian
- 汽车高斯曲面拟合 --- 2程序,以适应到表面二维高斯: 子= A *的进出口( -((西为X0)^2/2/sigmax^2 +(艺Y0的)^2/2/sigmay^ 2)。。)+ b的 这些例程是自动在某种意义上说,他们并不需要出发对模型参数的猜测规范。 autoGaussianSurfML(十一,彝,子)适合通过对模型参数的最大似然(最小二乘)。它首先计算了该模型在许多可能的参数值,然后选择最佳质量设置和细化与lsqcurvefit它。 auto
Untitled6
- it is to explain gibbs phenomenon
a
- 平移变换平移法(cycle_spinning)消除gibbs效应,相当有用的程序-The translation of the translation transform method eliminate gibbs effect
example1
- Metropolis within Gibbs sampling
Markov-Chain-Monte-Carlo
- Markov Chain Monte Carlo and gibbs sampling
pybblyzf
- 利用平移不变量发,实现小波阈值去噪,能够有效的消去伪吉布斯现象,利于后续的特征点提取。-The use of translation invariant issued to wavelet threshold denoising can effectively eliminate the Gibbs phenomenon, and conducive to the subsequent feature point extraction.
gibbs
- Gibbs Sampling 这个绝妙的想法在1953年被 Metropolis想到了,为了研究粒子系统的平稳性质, Metropolis 考虑了物理学中常见的波尔兹曼分布的采样问题,首次提出了基于马氏链的蒙特卡罗方法,即Metropolis算法,并在最早的计算机上编程实现。Metropolis 算法是首个普适的采样方法,并启发了一系列 MCMC方法,所以人们把它视为随机模拟技术腾飞的起点。 Metropolis的这篇论文被收录在《统计学中的重大突破》中, Metropolis算法也被遴选为二十
10.1-Gibbs-Sampling-From-Discrete-Undirected-Mode
- Gibbs sampling program