Description: Sequential Monte Carlo-Sequential Monte Carlo
Sequential Monte Carlo methods are a very general class of Monte Carlo methods
for sampling from sequences of distributions. Simple examples of these algorithms are
used very widely in the tracking and signal processing literature. Recent developments
illustrate that these techniques have much more general applicability, and can be applied
very effectively to statistical inference problems. Unfortunately, these methods are often
perceived as being computationally expensive and difficult to implement. This article
seeks to address both of these problems.
A C++ template class library for the efficient and convenient implementation of very
general Sequential Monte Carlo algorithms is presented. Two example applications are
provided: a simple particle filter for illustrative purposes and a state-of-the-art algorithm
for rare event estimation. Platform: |
Size: 478208 |
Author:marvin |
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Description: 对称Alpha稳定分布arima随机过程的产生与参数化谱估计M算法matlab程序-Symmetrical Alpha stable distributions of appearance and random process arima parametric spectral estimation M matlab algorithm
Platform: |
Size: 1024 |
Author:冯讯 |
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Description: 研究表明超高斯分布更加贴近语音信号的实际分布，然而语音信号很难用单一的概率密度
函数准确描述，针对这一情况，提出了一种用超高斯混合模型对语音信号幅度谱建模的新方法，并推导了
基于此模型的幅度谱最小均方误差估的估计式。仿真结果表明：与传统的短时谱估计算法相比，该算法不
仅能够进一步提高增强语音的信噪比，而且可以有效减小增强语音的失真度，提高增强语音的主观感知
质量。 -Recent research indicates that the speech spectral amplitude distributions could
be fairly described with super-Gaussian probability density function. However, the complexity
of speech signal determines that the distribution statistics ofspeech signal could not be well
described by single simple function. Thus a super-Gaussian mixture model for speech spectral
amplitude is proposed, and with this model, a minimum mean-square error (MMSE) estimator for speech
signals spectral amplitude is derived. The simulation results show that this algorithm based on
Gaussian and super-Gaussian speech model could achieve better noise suppression and lower speech
distortion as compared with the conventional short-time spectral amplitude estimation algorithm. Platform: |
Size: 957440 |
Author:立枣酒 |
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Search - estimation of distributions algorithm