Penczek P, Grochulski W
Methods Inf Med. 1989 Jul;28(3):160-7.
A multi-level scheme of syntactic reduction of the epileptiform EEG data is briefly discussed and the possibilities it opens up in describing the dynamic behaviour of a multi-channel system are indicated. A new algorithm for the inference of a Markov network from finite sets of sample symbol strings is introduced. Formulae for the time-dependent state occupation probabilities, as well as joint probability functions for pairs of channels, are given. An exemplary case of analysis in these terms, taken from an investigation of anticonvulsant drug effects on EEG seizure patterns, is presented.
简要讨论了癫痫样脑电图数据的多层次句法简化方案，并指出了该方案在描述多通道系统动态行为方面所开辟的可能性。介绍了一种从有限样本符号串集推断马尔可夫网络的新算法。给出了随时间变化的状态占据概率公式以及通道对的联合概率函数。给出了一个基于这些术语进行分析的示例，该示例取自抗惊厥药物对脑电图癫痫发作模式影响的研究。
