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Analysis of Interactions Among Hidden Components for Tucker Model

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Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/39656

Title: Analysis of Interactions Among Hidden Components for Tucker Model
Authors: Phan, Anh Huy Browse this author
Cichocki, Andrzej Browse this author
Issue Date: 4-Oct-2009
Publisher: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference, International Organizing Committee
Journal Title: Proceedings : APSIPA ASC 2009 : Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference
Start Page: 154
End Page: 158
Abstract: Tensor representation and tensor decompositions are natural approaches to deal with large amounts of data with multiple aspects and high dimensionality in modern applications, such as environmental analysis, chemometrices, pharmaceutical analysis, spectral analysis, neuroscience. The two most popular decomposition/factorization models for N-th order tensors are the Tucker model and the more restricted PARAFAC model. The Tucker decomposition allows for the extraction of different numbers of factors in each of the modes, and permits interactions within each modality while PARAFAC does not. This advantage, however, is also one of the weakness of this decomposition. The difficult problem is to identify the dominant relationships between components, and to establish unique representation. In this paper, we will introduce a new measure index which is called the Joint Rate (JR) index, in order to evaluate interactions among various components in the general Tucker decomposition. The Hinton diagram is also extended to 3-D visualization. The use of the JR index will be illustrated with the analysis of EEG data for classification and BCI applications.
Description: APSIPA ASC 2009: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference. 4-7 October 2009. Sapporo, Japan. Oral session: Advances in Signal Processing for Brain Data Analysis and Feature Extraction (5 October 2009).
Conference Name: APSIPA ASC 2009: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference
2009年アジア太平洋信号情報処理連合学会アニュアルサミット・国際会議
Conference Place: Sapporo
Type: proceedings
URI: http://hdl.handle.net/2115/39656
Appears in Collections:北海道大学サステナビリティ・ウィーク2009 (Sustainability Weeks 2009) > 2009年アジア太平洋信号情報処理連合学会アニュアルサミット・国際会議 (2009 APSIPA Annual Summit and Conference)

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