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EMfor_neural_networks
- In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial Co
EM_GM
- ％ EM algorithm for k multidimensional Gaussian mixture estimation ％ ％ Inputs: ％ X(n,d) - input data, n=number of observations, d=dimension of variable ％ k - maximum number of Gaussian components allowed ％ ltol - percentage of the log likeli
LDPC_BSN
- This LDPC software is intended as an introduction to LDPC codes computer based simulation. The pseudo-random irregular low density parity check matrix is based on Radford M. Neal’s programs collection, which can be found in [1]. While Neal’s collecti
LLR_compute
- 由4个.m文件组成，用于16QAM和64QAM调制的软信息的提取-By 4. M files for 16QAM and 64QAM modulation of the soft information extraction
Soft_demapping_8PSK
- soft Demapping 8PSK : LLR computation using Euclidian distance approach, Parallel-to-Serial converter, needs I and Q componets of 8PSK symbols at the input
ARMAKalman
- Several functions for evaluating the exact negative log-likelihood of ARMA models in O(n) time using the Kalman Filter
QPSK.LLR
- illustrates the improvement in BER performance when using log-likelihood instead of hard decision demodulation in a convolutionally coded communication link-illustrates the improvement in BER performance when using log-likelihood instead of hard d
MDL_segmenter
- em algorithm - Find approximate solution to Sf = conv(s,f) = d using EM iteration. EM seeks to minimize the Poisson negative log likelihood function J(f) = sum_i {[Sf]_i - (d_i + sigma^2)*log([Sf]_i + sigma^2)}. -em algorithm - Find approxim
EMALGORITHM
- In statistics, an expectation-maximization (EM) algorithm is a method for finding maximum likelihood or maximum a posteriori (MAP) estimates of parameters in statistical models, where the model depends on unobserved latent variables. EM is an iterati
fit_ML_maxwell
- fit_ML_normal - Maximum Likelihood fit of the log-normal distribution of i.i.d. samples!. Given the samples of a log-normal distribution, the PDF parameter is found fits data to the probability of the form: p(x) = sqrt(1/(2*pi))/(s*x)*
SFElikgarch
- 该程序代码，可以用于计算和描绘广义自回归异方差过程的条件对数似然函数。-SFElikgarch computes and plots values of the conditional log-likelihood function of a simulated GARCH(1,1) process
EMdemo
- EM算法在神经网络中的应用，可以用来进行视频数据分类。-In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Wil
SyntheticSpeechDetector
- computes inter frame differenc of log likelihood of calimed speaker s GMM.
softdectry
- This soft decoding algorithm for the sumproduct implementation of the ldpc codoes. The program calculates the log likelihood ratio. And add them all in the . After running the programme type Eji to fing the final matrix of lg likelyhood ratios.H=L
K_F_L.m
- Kalmen-Filter中最大似然函数的构造-formation of maximized log-likelihood function in Kalmen-Filter
Skewed_t_toolbox
- 偏态t分布分布函数，密度函数，对数似然函数，逆分布函数，随机模拟等等程序，对应学习偏态t分布的初学者特别适用-This zip file contains 5 functions: the pdf, cdf, log-likelihood, inverse cdf and a function to generate random draws the skewed t distribution.
bp
- LDPC码及其基于概率测度的和积译码算法.在此基础上对算法作融合,引入对数似然比概念,阐述了基于对数似然比测度的和积译码算法,对其校验节点消息传递实现技-LDPC codes based on their probability measure and product algorithm. Based on this algorithm for integration, the introduction of the log-likelihood ratio concept, elaborate
Logistic Regression
- 通过训练样本使用对数几率回归模型建模，并对测试样本类别进行预测(The training samples are modeled by log likelihood regression model, and then predicts the categories of test samples.)