| Paper: | SPTM-P9.5 | ||
| Session: | Signal Restoration, Reconstruction and Enhancement | ||
| Time: | Thursday, May 18, 14:00 - 16:00 | ||
| Presentation: | Poster | ||
| Topic: | Signal Processing Theory and Methods: Signal Restoration, Reconstruction, and Enhancement | ||
| Title: | Obtaining the Best Linear Unbiased Estimator of Noisy Signals by Non-Gaussian Component Analysis | ||
| Authors: | Masashi Sugiyama, Tokyo Institute of Technology, Japan; Motoaki Kawanabe, Gilles Blanchard, Fraunhofer FIRST.IDA, Germany; Vladimir Spokoiny, Weierstrass Institute and Humboldt University, Germany; Klaus-Robert Mueller, Fraunhofer FIRST.IDA / University of Potsdam, Germany | ||
| Abstract: | Obtaining the best linear unbiased estimator (BLUE) of noisy signals is a traditional but powerful approach to noise reduction. Explicitly computing BLUE usually requires the prior knowledge of the subspace to which the true signal belongs and the noise covariance matrix. However, such prior knowledge is often unavailable in reality, which prevents us from applying BLUE to real-world problems. In this paper, we therefore give a method for obtaining BLUE without such prior knowledge. Our additional assumption is that the true signal follows a non-Gaussian distribution while the noise is Gaussian. | ||
©2018 Conference Management Services, Inc. -||- email: webmaster@icassp2006.org -||- Last updated Friday, August 17, 2012