National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan.
PLoS One. 2012;7(3):e32352. doi: 10.1371/journal.pone.0032352. Epub 2012 Mar 1.
In time-resolved spectroscopy, composite signal sequences representing energy transfer in fluorescence materials are measured, and the physical characteristics of the materials are analyzed. Each signal sequence is represented by a sum of non-negative signal components, which are expressed by model functions. For analyzing the physical characteristics of a measured signal sequence, the parameters of the model functions are estimated. Furthermore, in order to quantitatively analyze real measurement data and to reduce the risk of improper decisions, it is necessary to obtain the statistical characteristics from several sequences rather than just a single sequence. In the present paper, we propose an automatic method by which to analyze composite signals using non-negative factorization and an information criterion. The proposed method decomposes the composite signal sequences using non-negative factorization subjected to parametric base functions. The number of components (i.e., rank) is also estimated using Akaike's information criterion. Experiments using simulated and real data reveal that the proposed method automatically estimates the acceptable ranks and parameters.
在时间分辨光谱学中，测量代表荧光材料能量转移的复合信号序列，并分析材料的物理特性。每个信号序列都由非负信号分量的和表示，这些信号分量由模型函数表示。为了分析测量信号序列的物理特性，需要估计模型函数的参数。此外，为了对真实测量数据进行定量分析并降低不当决策的风险，有必要从多个序列中获取统计特性，而不仅仅是单个序列。在本文中，我们提出了一种使用非负分解和信息准则分析复合信号的自动方法。所提出的方法使用参数基函数对复合信号序列进行非负分解。还使用赤池信息量准则（Akaike's information criterion）估计组件的数量（即秩）。使用模拟数据和真实数据的实验表明，该方法可以自动估计可接受的秩和参数。
