<--- Back to Details
First PageDocument Content
Signal processing / Singular value decomposition / Time series analysis / Principal component analysis / Independent component analysis / Global Positioning System / Statistics / Multivariate statistics / Data analysis
Date: 2014-01-22 12:17:03
Signal processing
Singular value decomposition
Time series analysis
Principal component analysis
Independent component analysis
Global Positioning System
Statistics
Multivariate statistics
Data analysis

TO Seminar, August 20, 2013 Adriano Gualandini, INGV Bologna, Italy Moving from Principal Component Analysis-based Inversion Method (PCAIM) to Independent Component Analysis-based Inversion Method (ICAIM) Abstract: Geode

Add to Reading List

Source URL: www.tectonics.caltech.edu

Download Document from Source Website

File Size: 27,27 KB

Share Document on Facebook

Similar Documents

Principal Component Analysis on non-Gaussian Dependent Data  Fang Han Johns Hopkins University, 615 N.Wolfe Street, Baltimore, MDUSA Han Liu Princeton University, 98 Charlton Street, Princeton, NJUSA

Principal Component Analysis on non-Gaussian Dependent Data Fang Han Johns Hopkins University, 615 N.Wolfe Street, Baltimore, MDUSA Han Liu Princeton University, 98 Charlton Street, Princeton, NJUSA

DocID: 1vdC9 - View Document

Generalized Principal Component Analysis (GPCA)∗ Ren´e Vidal† Yi Ma‡ Shankar Sastry† † Department of EECS, University of California, Berkeley, CA 94720

Generalized Principal Component Analysis (GPCA)∗ Ren´e Vidal† Yi Ma‡ Shankar Sastry† † Department of EECS, University of California, Berkeley, CA 94720

DocID: 1uYRE - View Document

A. Krisciukaitis et al.: Efficiency Evaluation of Autonomic Heart Control by Using the Principal Component Analysis of ECG P-Wave, en 9 en9  Efficiency Evaluation of Autonomic Heart Control by Using

A. Krisciukaitis et al.: Efficiency Evaluation of Autonomic Heart Control by Using the Principal Component Analysis of ECG P-Wave, en 9 en9 Efficiency Evaluation of Autonomic Heart Control by Using

DocID: 1tOkO - View Document

Full Regularization Path for Sparse Principal Component Analysis Alexandre d’Aspremont, Francis Bach & Laurent El Ghaoui, Princeton University, INRIA/ENS Ulm & U.C. Berkeley  Support from NSF, DHS and Google.

Full Regularization Path for Sparse Principal Component Analysis Alexandre d’Aspremont, Francis Bach & Laurent El Ghaoui, Princeton University, INRIA/ENS Ulm & U.C. Berkeley Support from NSF, DHS and Google.

DocID: 1tMMK - View Document

Binary Principal Component Analysis in the Netflix Collaborative Filtering Task

Binary Principal Component Analysis in the Netflix Collaborative Filtering Task

DocID: 1tMJC - View Document