Search for: source-parameters
Estimating the seismological source parameters of the 2006 Silakhor earthquake, Iran, using a Genetic Algorithm, Article 9th International Conference on Computational Structures Technology, CST 2008, Athens, 2 September 2008 through 5 September 2008 ; Volume 88 , 2008 ; 17593433 (ISSN); 9781905088232 (ISBN) ; Abbasnia, R ; Eslamian, Y ; Bozorgnasab, M ; Nicknam, A ; Sharif University of Technology
Civil-Comp Press 2008
The main objective of this article is to estimate the seismological source parameters of Silakhor earthquake which happened on March 31, 2006, in the southern part of Iran. The Empirical Green's Function approach was used for simulating the main shock and the well known Genetic Algorithm was utilized for modifying the seismological source parameters. The Kostrov slip function was adopted in the model due to its ability in more accurately modeling the rupture process. The selected station was sufficiently far away from the causative source so that the near source problems would not effect on the simulated time series. The GA process compares the elastic response spectra with 5% damping ratio,...
Minimizing the uncertainties of seismological-geotechnical source parameters using a genetic algorithm approach, Article 9th International Conference on Computational Structures Technology, CST 2008, Athens, 2 September 2008 through 5 September 2008 ; Volume 88 , 2008 ; 17593433 (ISSN); 9781905088232 (ISBN) ; Abbasnia, R ; Bozorgnasab, M ; Eslamian, Y ; Nicknam, A ; Sharif University of Technology
Civil-Comp Press 2008
The main purpose of this article is to estimate the seismological source parameters of the December 26, 2003, Bam earthquake Mw6.5 (Iran). The selected station is far away from the causative fault so that the synthesized ground motion would not be influenced by near source problems such as directivity effects. The well known Empirical Green's Functions (EGF) is used to synthesize the three components of main shock. The Kostrov slip model describing the entire rupture process was incorporated in the model. A generic algorithm (GA) technique is proposed for minimizing the differences between the synthesized time series and those of observed data. The estimated time series were validated by...
Article IEEE Transactions on Signal Processing ; Volume 57, Issue 11 , 2009 , Pages 4378-4390 ; 1053587X (ISSN) ; Babaie Zadeh, M ; Jutten, C ; Sharif University of Technology
We present a Bayesian approach for Sparse Component Analysis (SCA) in the noisy case. The algorithm is essentially a method for obtaining sufficiently sparse solutions of underdetermined systems of linear equations with additive Gaussian noise. In general, an underdetermined system of linear equations has infinitely many solutions. However, it has been shown that sufficiently sparse solutions can be uniquely identified. Our main objective is to find this unique solution. Our method is based on a novel estimation of source parameters and maximum a posteriori (MAP) estimation of sources. To tackle the great complexity of the MAP algorithm (when the number of sources and mixtures become large),...