A singular value decomposition based approach for far-field reconstruction from irregularly spaced planar wide-mesh scanning data

2007 ◽  
Vol 49 (7) ◽  
pp. 1768-1772 ◽  
Author(s):  
F. D'Agostino ◽  
F. Ferrara ◽  
C. Gennarelli ◽  
R. Guerriero ◽  
M. Migliozzi ◽  
...  
Keyword(s):  
Singular Value Decomposition ◽  
Singular Value ◽  
Far Field ◽  
Field Reconstruction ◽  
Value Decomposition

scholarly journals A Truncated Singular Value Decomposition Enhanced Nested Complex Source Beam Method

2017 ◽  
Vol 2017 ◽  
pp. 1-7
Author(s):  
Lianning Song ◽  
Zaiping Nie
Keyword(s):  
Singular Value Decomposition ◽  
Radiation Power ◽  
Singular Values ◽  
Beam Width ◽  
Singular Value ◽  
Far Field ◽  
Truncated Singular Value Decomposition ◽  
Complex Source ◽  
Equivalent Sources ◽  
Value Decomposition

This work presents a novel matrix compression algorithm to improve the computational efficiency of the nested complex source beam (NCSB) method. The algorithm is based on the application of the truncated singular value decomposition (TSVD) to the multilevel aggregation, translation, and disaggregation operations in NCSB. In our implementation, the aggregation/disaggregation matrices are solved by the truncated far-field matching, which is based on the directional far-field radiation property of the complex source beams (CSBs). Furthermore, the translation matrices are obtained according to the beam width of CSBs. Due to the high directivity of the radiation patterns of CSBs, all the far-field related interaction matrices are low-ranked. Therefore, TSVD can be employed and a new set of equivalent sources can be constructed by a linear combination of the original CSBs. It is proved that the radiation power of the new sources is proportional to the square of the corresponding singular values. This provides a theoretical guideline to drop the insignificant singular vectors in the calculation. In doing so, the efficiency of the original NCSB method can be much improved while a reasonably good accuracy is maintained. Several numerical tests are conducted to validate the proposed method.

A New Modified SVD Method Applied in 3D Acoustic Temperature Field Reconstruction

2013 ◽  
Vol 732-733 ◽  
pp. 218-223 ◽  
Author(s):  
Wei Yang ◽  
Xiao Liang Zhu
Keyword(s):  
Temperature Field ◽  
Singular Value Decomposition ◽  
Singular Values ◽  
Singular Value ◽  
Temperature Fields ◽  
Time Data ◽  
Field Reconstruction ◽  
Value Decomposition ◽  
Svd Method ◽  
Temperature Field Reconstruction

In order to solve the ill-posed problem in 3D acoustic temperature field reconstruction, the paper proposed a new modified singular value decomposition (SVD) method.According to their reliability ,singular values were divided into three parts and got various degree of modification respectively. To verify the performance of the new algorithm based on the modified SVD method,two model temperature fields were reconstructed when the signal-to-noise ratio (SNR) of sound flight-time data was 50dB , 40dB and 30dB respectively.And the results were compared with those based on routine Truncated singular value decomposition (TSVD) and Tikhonov methods. Simulation results show that the new algorithm has higher precision, better anti-noise ability than the routine methods and it is more suitable for the complex temperature fields reconstruction, thus it is expected to be used for temperature field reconstruction on-line.

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