The Critical Study of Mutual Coherence Properties on Compressive Sensing Framework for Sparse Reconstruction Performance: Compression vs Measurement System
Compressive Sensing (CS) framework becomes well known since its ability to recover
signal only by using less sampling required by Shanon-Nyquist theorem. The lack of required
sampling is no longer constraint for having good reconstruction performance. The load is shifted
to the reconstruction procedure instead of the sampling acquisition process. As long as the signal
can be guaranteed sparse, the CS based method is able to provide high reconstruction accuracy.
One of the CS principle is incoherence property, which can be represented by mutual coherence
value. It represents the coherence between the sensing matrix and the sparse base dictionary. The
theory said the less coherence between those two parameters, the more precise the reconstruction
is. In fact, it is not consistently applied. The research presented on this paper find that, the theory
is consistent for reconstruction on compression system, while it is not applied on the
reconstruction of measurement system. Other properties are found to be more representative on
assigning necessary condition for reconstruction performance on measurement system
Detail Information
| Bagian |
Informasi |
| Pernyataan Tanggungjawab |
|
| Pengarang |
Nur Afny Catur Andriyani - Personal Name
|
| Edisi |
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| No. Panggil |
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| Subyek |
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| Klasifikasi |
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| Judul Seri |
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| GMD |
Informatic Engineering |
| Bahasa |
English |
| Penerbit |
Universitas Indonesia |
| Tahun Terbit |
2020 |
| Tempat Terbit |
Depok |
| Deskripsi Fisik |
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| Info Detil Spesifik |
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Citation
. (2020).The Critical Study of Mutual Coherence Properties on Compressive Sensing Framework for Sparse Reconstruction Performance: Compression vs Measurement System.(Electronic Thesis or Dissertation). Retrieved from https://localhost/etd
