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sparse bayesian
Vertaling van "sparse bayesian" in Chinees
稀疏贝叶斯
In this paper, we propose a new agent identification method by using a sparse Bayesian model.
本文我们提出一种采用稀疏贝叶斯模型的全新药剂识别方法。
A new agent identification method using a sparse Bayesian model has been introduced and investigated in this paper.
本文介绍和研究了一种使用稀疏贝叶斯模型的新药剂识别方法。
In Appendix C, we prove that in the updating procedure of the sparse Bayesian method, forcing the negative abundance estimations to zero will not change the convergence of the iteration.
在附录 C 中，我们证明在稀疏贝叶斯方法的更新过程中，迫使负丰度估算值为零不会改变迭代的收敛性。
In Section II, the agent identification scheme using a sparse Bayesian model is described, along with a discussion on how to address the issue of signature mismatch.
在第二节，我们描述了使用稀疏贝叶斯模型的药剂识别，并讨论了如何解决特征不匹配的问题。
Using a sparse Bayesian model, our proposed method obtains an estimate of the abundance fraction vector with only a few nonzero entries, and the zero entries of the estimate can be interpreted as the absence of certain agents.
我们使用稀疏贝叶斯模型提出的方法，获得了只有几个非零实体的丰度值向量估计值，而估计值的零实体解释为缺乏某些药剂。
Index Terms-Agent identification, false alarm, linear mixture, mismatch, signature, sparse Bayesian model, spectral sensing.
索引术语 - 药剂识别、误报、线性混合、不匹配、签名、稀疏贝叶斯模型、光谱遥感。
In our numerical studies, the abundance fractions of agents are estimated by the following methods: the sparse Bayesian model (SBM) using the noninformative hyperprior and taking into account the nonnegativity of the abundance fractions, as described in Section II-D, the NCLS algorithm and the orthogonal matching pursuit (OMP) method.
在我们的数值研究中，使用以下方法估算药剂的丰度值：使用非信息超先验的稀疏贝叶斯模型 （SBM），考虑丰度值的非负性，如第II-D节，NCLS算法和正正交匹配追踪方法所述。
Therefore, in the following sections, we choose and in the sparse Bayesian model to estimate the abundance fraction vector.
因此，在下面的章节中，我们在系数贝叶斯模型中选择和估算丰度向量。
Synoniemen voor sparse bayesian in het Engels
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