Author/Authors :
al-hasanat, abdullah university of al-hussien bin talal - faculty of engineering - dept. of computer engineering, Jordan , mesleh, abdelwadood al-balqa’ applied university - faculty of engineering technology - computer engineering dept., Jordan , krishan, monther al-balqa’ applied university - faculty of engineering technology - mechatronics engineering dept., Jordan , sharadqh, ahmed al-balqa’ applied university - faculty of engineering technology - computer engineering dept., Jordan , al-qaisi, aws al-balqa’ applied university - faculty of engineering technology - communication engineering dept., Jordan , woo, w.l. newcastle university - school of electrical, electronic computer engineering, uk , dlay, s.s. newcastle university - school of electrical, electronic computer engineering, uk
Abstract :
This paper presents a blind separation algorithm based on singular value decomposition (SVD) of reduced dimension spectral matrix. Furthermore, a mathematical matrix model of the multicomponent seismic wavefield is developed as a framework for implementing the proposed algorithm. The proposed blind separation algorithm organizes the frequency transformed multicomponent seismic wavefield into one long data vector. The blind separation of the desired seismic wavefield is accomplished by projecting the long data vector onto the eigenvectors of the dimensionally reduced spectral matrix according to the energy of the eigenvalues. The proposed algorithm is tested on both synthetic and real multicomponent seismic wavefields. Results show outstanding performance compared to the MC-WBSMF algorithm. Therefore, the computational complexity is reduced by a factor greater than 14,400 and there is an improvement in accuracy of 17.5%.
