2016.12.12
2016年12月15日に久留米大学バイオ統計センター公開セミナーを開催します。
バイオ統計センター公開セミナー
日時：2016年12月15日（木）15:00-17:00
場所：久留米大学バイオ統計センター 講義室
講演者： Prof. Young K. Truong (Department of Biostatistics, The University of North Carolina at Chapel Hill)
演題：「Independent Colored Sources Extraction」
概要： Independent component analysis (ICA) plays an important role in Blind Source Separation (BSS) problems. In many applications, multichannel data or sensor biological observations are often acquired through some recording devices, with each sensor receiving different mixed source signals. Both the sources and the mixing mechanism are usually unknown, but are related to the observations through which they will be learned or extracted. Given a sequence of the observations, we will present a statistical model and an R package for learning the sources and the mixing mechanism. The algorithms for extraction and their principles will be illustrated based on simulated data. Applications involving spatial and temporal signal analysis will be given in terms of EEG and mobile telephone data.
場所：久留米大学バイオ統計センター 講義室
講演者： Prof. Young K. Truong (Department of Biostatistics, The University of North Carolina at Chapel Hill)
演題：「Independent Colored Sources Extraction」
概要： Independent component analysis (ICA) plays an important role in Blind Source Separation (BSS) problems. In many applications, multichannel data or sensor biological observations are often acquired through some recording devices, with each sensor receiving different mixed source signals. Both the sources and the mixing mechanism are usually unknown, but are related to the observations through which they will be learned or extracted. Given a sequence of the observations, we will present a statistical model and an R package for learning the sources and the mixing mechanism. The algorithms for extraction and their principles will be illustrated based on simulated data. Applications involving spatial and temporal signal analysis will be given in terms of EEG and mobile telephone data.
