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人工智能/神经网络 The EM algorithm is short for Expectation-Maximization algorithm. It is based on an iterative optimi
The EM algorithm is short for Expectation-Maximization algorithm. It is based on an iterative optimization of the centers and widths of the kernels. The aim is to optimize the likelihood that the given data points are generated by a mixture of Gaussians. The numbers next to the Gaussians give the re ...
行业发展研究 A one-dimensional calibration object consists of three or more collinear points with known relative
A one-dimensional calibration object consists of three or more collinear points with known relative positions.
It is generally believed that a camera can be calibrated only when a 1D calibration object is in planar motion or rotates
around a &macr xed point. In this paper, it is proved that when a m ...
文件格式 In this article, we present an overview of methods for sequential simulation from posterior distribu
In this article, we present an overview of methods for sequential simulation from posterior distributions.
These methods are of particular interest in Bayesian filtering for discrete time dynamic models
that are typically nonlinear and non-Gaussian. A general importance sampling framework is develop ...
matlab例程 Adaptive Filter. This script shows the BER performance of several types of equalizers in a static ch
Adaptive Filter. This script shows the BER performance of several types of equalizers in a static channel with a null in the passband. The script constructs and implements a linear equalizer object and a decision feedback equalizer (DFE) object. It also initializes and invokes a maximum likelihood s ...
matlab例程 自己编的matlab程序。用于模式识别中特征的提取。是特征提取中的Sequential Forward Selection方法
自己编的matlab程序。用于模式识别中特征的提取。是特征提取中的Sequential Forward Selection方法，简称sfs.它可以结合Maximum-Likelihood-Classifier分类器进行使用。
matlab例程 In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve r
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 College). The data and simulations are described in: ...
单片机开发 This LDPC software is intended as an introduction to LDPC codes computer based simulation. The pseud
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 collection is well documented, in my opinion, C source c ...
其他书籍 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 simu
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 ...
matlab例程 ％ EM algorithm for k multidimensional Gaussian mixture estimation ％ ％ Inputs: ％ X(n,d) - input da
％ 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 likelihood difference between 2 iterations ([] for none)
％ ...
matlab例程 This LDPC software is intended as an introduction to LDPC codes computer based simulation. The pseud
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 collection is well documented, in my opinion, C source c ...