gibbs sampler

A group-blind multiuser detection technique based on Gibbs sampler

基于Gibbs采样的群盲多用户检测技术

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To generate the sample by Gibbs sampler, we first derive all of the conditional posterior distributions.

由于参数联合后验密度的复杂性，我们导出了所有的条件后验分布，以便利用Gibbs抽样器方法抽取后验密度的样本。

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The models were estimated via Gibbs sampler with data augmentation by a mixture of standard exponential distribution and standard normal distribution to represent the asymmetric Laplace distribution.

由于模型参数的后验条件分布没有确定的分布形式，通过数据扩充得到参数的完全条件分布从而实现模型参数的贝叶斯估计。

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So a new multitarget tracking algorithm is proposed, which combines the particle filter and the Gibbs sampler, and can track maneuvering multitarget in cluttered environment very well.

提出了一种结合粒子滤波器和吉布斯采样器的多机动目标跟踪算法，可以很好地解决在杂波环境下的多机动目标跟踪问题。

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