Spectral decomposition in multichannel recordings based on multivariate parametric identification
Spectral decomposition in multichannel recordings based on multivariate parametric identification
复制标题
DOI：
10.1109/10.641336
复制
发表时间：
1997-11-01
影响因子：
4.6
通讯作者：
Cerutti, S
中科院分区：
文献类型：
--
作者：
Baselli, G;Porta, A;Cerutti, S
提出了一种多通道记录的频谱分解方法，它从不同振荡机制的分类和量化的角度来表示多变量(MV)参数识别的结果。为此，定义了一类MV动态调整(MDA)模型，其中因果相互作用的MV自回归(MAR)网络由不相关自回归(AR)过程馈送。与MAR网络闭环相互作用相关的极点(CL-极点)和与每个AR输入相关的极点被解缠并相应地分类。每个通道的自谱可以被划分为部分频谱，每个频谱与一个输入相关。每个部分谱受CL极点和相应输入极点的影响，从而利用残差法将其分解成相应的分量。因此，不同的振荡机制，即使在相似的频率下，也按不同的极点进行分类，并按相应的分量进行量化。模型的结构非常灵活，可以适应各种可用信号集合和关于已有相互作用的先验假设；提出了一种强调振荡源和相应的闭环系统相互作用的图形布局。简要说明了与心血管变异性相关的应用实例。
A method of spectral decomposition in multichannel recordings is proposed, which represents the results of multivariate (MV) parametric identification in terms of classification and quantification of different oscillating mechanisms. For this purpose, a class of MV dynamic adjustment (MDA) models in which a MV autoregressive (MAR) network of causal interactions is fed by uncorrelated autoregressive (AR) processes is defined. Poles relevant to the MAR network closed-loop interactions (cl-poles) and poles relevant to each AR input are disentangled and accordingly classified. The autospectrum of each channel can be divided into partial spectra each relevant to an input. Each partial spectrum is affected by the cl-poles and by the poles of the corresponding input; consequently, it is decomposed into the relevant components by means of the residual method. Therefore, different oscillating mechanisms, even at similar frequencies, are classified by different poles and quantified by the corresponding components. The structure of MDA models is quite flexible and can be adapted to various sets of available signals and a priori hypotheses about the existing interactions; a graphical layout is proposed that emphasizes the oscillation sources and the corresponding closed-loop interactions. Application examples relevant to cardiovascular variability are briefly illustrated.