Art

J-GLOBAL ID：202102272128746001   Reference number：21A0217705

The LMS-Type Adaptive Filter Based on the Gaussian Model for Controlling the Variances of Coefficients

係数の分散を制御するためのGaussモデルに基づくLMS型適応フィルタ

Author (1)： NISHIKAWA Kiyoshi (Faculty of Systems Design, Tokyo Metropolitan University)
Material： IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (Web)  (IEICE Trans Fundam Electron Commun Comput Sci (Web))
Volume： E103.A  Issue： 12  Page： 1494-1502(J-STAGE)  Publication year： 2020 
JST Material Number： U0466A  ISSN： 1745-1337  Document type： Article
Article type： 原著論文  Country of issue： Japan (JPN)  Language： ENGLISH (EN)

Thesaurus term： coefficient ,  variance ,  control ,  *Gaussian model ,  *computer application system ,  *adaptive filter ,  normal distribution ,  variable ,  mean value ,  distribution ,  renewal ,  Computer Simulation ,  computer application ,  utilization
Semi thesaurus term： *GMM ,  Gaussian distribution ,  Gaussian mixture model ,  *Learning Management System ,  random variable

Author keywords (4)： Gaussian model ,  LMS adaptive filter ,  Gaussian mixture model ,  system identification

JST classification (2)： Digital filter  (NC04022Z) ,  Artificial intelligence  (JE08000Z)

Reference (31)：

• [1] C. Stauffer and W.E.L. Grimson, “Adaptive background mixture models for real-time tracking,” Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on., vol.2, p.252 1999. 10.1109/cvpr.1999.784637
• [2] D.A. Reynolds and R.C. Rose, “Robust text-independent speaker identification using gaussian mixture speaker models,” IEEE Trans. Speech Audio Process., vol.3, no.1, pp.72-83, Jan. 1995. 10.1109/89.365379
• [3] W.M. Campbell, D.E. Sturim, and D.A. Reynolds, “Support vector machines using GMM supervectors for speaker verification,” IEEE Signal Process. Lett., vol.13, no.5, pp.308-311, May 2006. 10.1109/lsp.2006.870086
• [4] K. Nishikawa, Y. Yamashita, T. Yamaguchi, and T. Nishitani, “Consideration on performance improvement of shadow and reflection removal based on GMM,” 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA), pp.1-7, Dec. 2016. 10.1109/apsipa.2016.7820902
• [5] C.M. Bishop, Pattern Recognition and Machine Learning (Information Science and Statistics), Springer-Verlag, Berlin, Heidelberg, 2006.

Terms in the title (4)： 係数 ,  Gaussモデル ,  LMS ,  適応フィルタ