Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (Journal of the Korea Institute of Information and Communication Engineering)
Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
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¿µ¹®Á¦¸ñ(English Title) |
Performance Comparison of Structured Measurement Matrix for Block-based |
ÀúÀÚ(Author) |
·ùÁß¼±
±èÁø¼ö
Joong-seon Ryu
Jin-soo Kim
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¿ø¹®¼ö·Ïó(Citation) |
VOL 20 NO. 08 PP. 1452 ~ 1459 (2016. 08) |
Çѱ۳»¿ë (Korean Abstract) |
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¿µ¹®³»¿ë (English Abstract) |
Compressed sensing is a signal processing technique for efficiently acquiring and reconstructing in and under Nyquist rate representation. Generally, the measurement prediction usually works well with a small block while the quality of recovery is known to be better with a large block. In order to overcome this dilemma, conventional research works use a structural measurement matrix with which compressed sensing is done in a small block size but recovery is performed in a large block size. In this way, both prediction and recovery are made to be improved at same time. However, the conventional researches did not compare the performances of the structural measurement matrix, affected by the block size. In this paper, by expanding a structural measurement matrix of conventional works, their performances are compared with different block sizes. Experimental results show that a structural measurement matrix with 4x4 Hadamard transform matrix provides superior performance in block size 4.
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Å°¿öµå(Keyword) |
¾ÐÃ༾½Ì
±¸Á¶ÈµÈ ÃøÁ¤ Çà·Ä
BCS-SPL
ÇÏ´Ù¸¶µå Çà·Ä
Compressed sensing
Structured measurement matrix
BCS-SPL
Hadamard matrix
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