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Covariance Matrix of a Probability Distribution for Image Dictionaries in Compressed Sensing
Toshiaki Aida 제어로봇시스템학회 2018 제어로봇시스템학회 국제학술대회 논문집 Vol.2018 No.10
Sparse representation is one of the principles for the most effective signal processing, and makes it possible for us to infer from less data. The framework of signal processing based on it is called compressed sensing or compressive sensing, where dictionary matrices play an essential role of the basis for sparse representation. In our previous work, we successfully derived an analytical expression of the probability distribution followed by image dictionaries for the images generated by the Gaussian model [1]. However, we have found that the distribution has a difficulty of a divergent covariance matrix, which is needed for an analytical performance evaluation of image processing by compressed sensing. Therefore, it is the purpose of this paper to solve the difficulty and to open the way to the evaluation.
Compressed Sensing for Phase Unwrapping of Interferometric SAR Data
Toshiaki Aida 제어로봇시스템학회 2017 제어로봇시스템학회 국제학술대회 논문집 Vol.2017 No.10
We approach to the problem of wave-front reconstruction via phase unwrapping of interferograms observed by interferometric synthetic aperture radar (SAR), from the viewpoints of Bayesian statistical inference and compressed sensing. For this purpose, we apply sparse representation for compressed sensing to the Bayesian wave-front reconstruction model from SAR interferograms by Saika and Uezu [1]. In the formulation of the problem taking sparse representation into account, the MAP estimate is found to lead to a phase unwrapping algorithm which can be interpreted as a quadratic programming problem. Numerical experiments on an artificial wave-front make it clear that the algorithm effectively removes noise to reconstruct the wave-front, although it suffers from the errors similar to block noise in image processing.
Toshiaki Taniike,Shougo Takahashi,Toru Wada,Iku Kouzai,Minoru Terano 한국고분자학회 2010 Macromolecular Research Vol.18 No.9
The dispersion state of surface Ti species is one of the most important factors affecting the polymerization properties of MgCl2-supported heterogeneous Ziegler-Natta catalysts. In this paper, ethylene-propylene copolymerization was carried out using a novel Ziegler-Natta model catalyst with “isolated” and “clustered” TiCl3 molecules on MgCl2. At a lower ethylene/propylene feed ratio, the dispersion state of the Ti species strongly affected both the composition and sequence distribution of the copolymers. The “isolated” Ti species gave a relatively random copolymer, and clustering of Ti species enhanced the bulkiness. The addition of an external donor basically deteriorated the random copolymerization character of the “isolated Ti species but the degree of deterioration depended on the type of donors. On the other hand, the balance between the monomer feed and consumption dominated the copolymerization performance at a higher ethylene/propylene feed ratio to obscure the effects of the dispersion state.
Measuring Multipath Error of a Pseudo Quasi-Zenith Satellite
Toshiaki Tsujii,Hiroshi Tomita,Yoshinori Okuno,Ivan Petrovski,Masahiro Asako,Kazuki Okano 한국항해항만학회 2006 한국항해항만학회 학술대회논문집 Vol.2 No.-
Japan has been investigating a new satellite based positioning system called Quasi-Zenith Satellite System (QZSS). Since the improvement of positioning availability in urban area is one of the most important advantages of the QZSS, multipath mitigation is a key factor for the QZSS positioning system. Therefore, Japan Aerospace Exploration Agency (JAXA) and GNSS Inc. have commenced the R&D of a pseudolite, which transmits the next-generation signal such as BOC(1,1), in order to evaluate the effect of multipath on the new signal. A prototype BOC pseudolite was developed in 2005, and ground tests showed a capability of generating proper pseudorange. Also, preliminary flight experiments using a pseudo quasi-zenith satellite, a helicopter on which the pseudolite is installed, were conducted in early 2006, and the BOC-type correlation function was monitored in real time.