Bernoulli-Gaussian spectral analysis of unevenly spaced astrophysical data
Bernoulli-Gaussian spectral analysis of unevenly spaced astrophysical data
复制标题
不均匀间隔天体物理数据的伯努利-高斯谱分析
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
H. Carfantan
中科院分区：
文献类型：
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作者：
S. Bourguignon;H. Carfantan
我们解决的问题，线光谱检测和估计从天体物理数据。由于观测通常会受到采样不规则性的影响，傅立叶频谱中可能会出现假峰。我们提出了一个线性谱模型与任意大量的固定频率和搜索稀疏的解决方案，通过建模的频谱作为一个Bernoulli-Gaussian过程。使用马尔可夫链蒙特卡罗方法计算后验均值估计讨论了在无监督的框架。对Cheng等人（1996）的原始工作进行了修改，以说明谱分析问题的特殊性。仿真结果表明，该方法的效率和它的相关性的天体物理频率检测上下文被强调。最后，给出了一个天体物理数据的应用
We address the problem of line spectra detection and estimation from astrophysical data. As observations generally suffer sampling irregularities, false peaks may appear in the Fourier spectrum. We propose a linear spectral model with an arbitrarily large number of fixed frequencies and search for a sparse solution by modelling the spectrum as a Bernoulli-Gaussian process. The use of Markov chain Monte Carlo methods to compute the posterior mean estimate is discussed in the unsupervised framework. The original work by Cheng et al. (1996) is modified to account for specificities of the spectral analysis problem. Simulations reveal the efficiency of the method and its relevance to the astrophysical frequency detection context is emphasized. Finally, an application to astrophysical data is presented