• ETRI Journal
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• v.42 no.6
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• pp.815-826
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• 2020

We propose a two-dimensional (2D) scattering-center-extraction (SCE) method using sparse recovery based on the compressive-sensing theory, even with data missing from the received radar cross-section (RCS) dataset. First, using the proposed method, we generate a 2D grid via adaptive discretization that has a considerably smaller size than a fully sampled fine grid. Subsequently, the coarse estimation of 2D scattering centers is performed using both the method of iteratively reweighted least square and a general peak-finding algorithm. Finally, the fine estimation of 2D scattering centers is performed using the orthogonal matching pursuit (OMP) procedure from an adaptively sampled Fourier dictionary. The measured RCS data, as well as simulation data using the point-scatterer model, are used to evaluate the 2D SCE accuracy of the proposed method. The results indicate that the proposed method can achieve higher SCE accuracy for an incomplete RCS dataset with missing data than that achieved by the conventional OMP, basis pursuit, smoothed L0, and existing discrete spectral estimation techniques.

• ETRI Journal
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• v.45 no.3
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• pp.492-504
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• 2023

Researchers have recently shown an increased interest in estimating the direction-of-arrival (DOA) of wideband noncircular sources, but existing studies have been restricted to subspace-based methods. An off-grid sparse recovery-based algorithm is proposed in this paper to improve the accuracy of existing algorithms in low signal-to-noise ratio situations. The covariance and pseudo covariance matrices can be jointly represented subject to block sparsity constraints by taking advantage of the joint sparsity between signal components and bias. Furthermore, the estimation problem is transformed into a single measurement vector problem utilizing the focused operation, resulting in a significant reduction in computational complexity. The proposed algorithm's error threshold and the Cramer-Rao bound for wideband noncircular DOA estimation are deduced in detail. The proposed algorithm's effectiveness and feasibility are demonstrated by simulation results.

• The Journal of the Acoustical Society of Korea
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• v.37 no.1
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• pp.39-45
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• 2018

Compressive sensing allows recovering an original signal which has a small dimension of the signal compared to the dimension of the entire signal in a short period of time through a small number of observations. In this paper, we proposed a method for detecting tonal signal which caused by the machinery component of a vessel such as an engine, gearbox, and support elements. The tonal signal can be modeled as the sparse signal in the frequency domain when it compares to whole spectrum range. Thus, the target tonal signal can be estimated by S-OMP (Simultaneous-Orthogonal Matching Pursuit) which is one of the sparse signal recovery algorithms. In simulation section, we showed that S-OMP algorithm estimated more precise frequencies than the conventional FFT (Fast Fourier Transform) thresholding algorithm in low SNR (Signal to Noise Ratio) region.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.10
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• pp.29-39
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• 2008

Greedy routing which is easy to apply to geographic wireless sensor networks is frequently used. Greedy routing works well in dense networks whereas in sparse networks it may fail. When greedy routing fails, it needs a recovery algorithm to get out of the communication void. However, additional recovery algorithm causes problems that increase both the amount of packet transmission and energy consumption. Communication void is a condition where all neighbor nodes are further away from the destination than the node currently holding a packet and it therefore cannot forward a packet using greedy forwarding. Therefore we propose a VODUA(Virtually Ordered Distance Upgrade Algorithm) as a novel idea to improve and solve the problem of void. In VODUA, nodes exchange routing graphs that indicate information of connection among the nodes and if there exist a stuck node that cannot forward packets, it is terminated using Distance Cost(DC). In this study, we indicate that packets reach successfully their destination while avoiding void through upgrading of DC. We designed the VODUA algorithm to find valid routes through faster delivery and less energy consumption without requirement for an additional recovery algorithm. Moreover, by using VODUA, a network can be adapted rapidly to node's failure or topological change. This is because the algorithm utilizes information of single hop instead of topological information of entire network. Simulation results show that VODUA can deliver packets from source node to destination with shorter time and less hops than other pre-existing algorithms like GPSR and DUA.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.638-641
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• 2008

Geothermal water at moderate temperature in a range between 30 to $50^{\circ}C$ exists sparse in surroundings. Mostly they are utilized as heat or water source at spar zones in Korea. However, a large portion of used water is discarded due to its poor recovery quality and inferior application technologies. In this research, an innovative heat pump system based on the hybrid concept that combinate compression cycle and absorption cycle was investigated mathematically. The hybrid heat pump aims to recycle various kind of the heat sources at moderate temperature including geothermal water effectively. The prime objective of the simulation is to design a compression/absorption hybrid heat pump system which can make high temperature above the level of $90^{\circ}C$ and low temperature of $20^{\circ}C$ as well at the same using $50^{\circ}C$ geothermal heat water. As a result, primitive data was provided as a basis to design a prototype 3 RT class hybrid heat pump.

• Quantitative Bio-Science
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• v.37 no.2
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• pp.133-141
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• 2018

Graphical lasso is one of the most popular methods to estimate a sparse precision matrix, which is an inverse of a covariance matrix. The objective function of graphical lasso imposes an ${\ell}_1$-penalty on the (vectorized) precision matrix, where a tuning parameter controls the strength of the penalization. The selection of the tuning parameter is practically and theoretically important since the performance of the estimation depends on an appropriate choice of tuning parameter. While information criteria (e.g. AIC, BIC, or extended BIC) have been widely used, they require an asymptotically unbiased estimator to select optimal tuning parameter. Thus, the biasedness of the ${\ell}_1$-regularized estimate in the graphical lasso may lead to a suboptimal tuning. In this paper, we propose a two-staged bias-correction procedure for the graphical lasso, where the first stage runs the usual graphical lasso and the second stage reruns the procedure with an additional constraint that zero estimates at the first stage remain zero. Our simulation and real data example show that the proposed bias correction improved on both edge recovery and estimation error compared to the single-staged graphical lasso.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1313-1320
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• 2015

In this paper, we propose a user detection technique based on parallel orthogonal matching pursuit (POMP) for uplink multi-user random access networks (RANs) with a number of users and receiver antennas. In general RANs, it is difficult to estimate the number of users simultaneously transmitting packets at the receiver because users with data send the data without grant of BS. In this paper, therefore, we modify the original POMP for the RAN and evaluate its performances through extensive computer simulations. Simulation results show that the proposed POMP can effectively detect activated users more than about 2%~8% compared with the conventional OMP in RANs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.1
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• pp.25-30
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• 2017

Millimeter wave (mmWave) bands are expected to improve date rate of 5G systems due to the wide available bandwidth. While severe path loss in those bands has impeded the utilization, short wavelength enables a large number of antennas packed in a compact form, which can mitigate the path loss. However, estimating the channel with a conventional scheme requires a huge training overhead, hence an efficient estimation scheme operating with a small overhead needs to be developed. The sparsity of mmWave channels caused by the limited scatterers can be exploited to reduce the overhead by utilizing compressed sensing. In this paper, we introduce compressed sensing techniques for mmWave channel estimation. First, we formulate wideband channel estimation into a sparse recovery problem. We also analyze the characteristics of random measurement matrix constructed using quantized phase shifters in terms of mutual incoherence.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.1249-1254
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• 2008

Industrial low temperature waste heat exists sparse in surroundings but its amount is huge. However, large portion of waste heat is discarded due to its poor recovery quality and inferior application technologies. The heat pump system in this research is based on the hybrid combination of compression cycle and absorption cycle in order to recycle various kind of industrial waste heat effectively. The prime objective is to design a compression absorption hybrid heat pump system which can produce high temperature above the level of $90^{\circ}C$ and low temperature of $20^{\circ}C$ at the same time using waste heat water of $50^{\circ}C$. A mathematical simulation was carried out as a basis to design a prototype 3 RT class hybrid heat pump. From the simulation results, fundamental parameters to design the system were obtained.

• Journal of the korean academy of Pediatric Dentistry
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• v.42 no.2
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• pp.180-187
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• 2015

Incontinentia pigmenti, also called Bloch-Sulzberger syndrome, is a rare X-linked inherited dominant disorder that affects females, but causes spontaneous abortion of prenatal males. Incontinentia pigmenti is a systemic disease with clinical features similar to ectodermal dysplasia, including congenitally missing teeth. The pathogenesis is related to gene mutations in NF-kappa-B essential modulator on chromosome Xq28. Incontinentia pigmenti is caused by a defect in the developmental stage of organs originating from the ectoderm or mesoderm and involves the skin, eyes, hair, teeth and central nervous system. This report discusses the management of three cases of 3 to 5 years old females with incontinentia pigmenti and accompanying multiple missing teeth. The cases had sparse hair, and showed oligodontia and anomalous crowns with supplementary cusps in the posterior teeth and conical anterior teeth. Removable space maintainers were applied, achieving improved esthetics, recovery of mastication and increased self-esteem in the patients.