• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.138-144
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• 2012

In this paper, we introduce the time-domain equalizer in orthogonal frequency division multiplexing (OFDM) systems using orthogonal matching pursuit (OMP) algorithm. Since OFDM system inserts guard intervals, it shows robust performance against multi-path fading. However, in Doppler channel, inter-carrier interference (ICI) occurs because an orthogonality of sub-carriers does not maintain. A least squares (LS) algorithm is common method of time-domain equalizer, but if a channel length is longer, the performance deteriorates by noise. The multi-path fading is a summation of the different delay signal. And that has sparse properties in time-domain. Because the OMP algorithm of the compressive sensing (CS) algorithm restores the channel by choosing the important elements of sparse channel, it can reduce the influence of noise. We simulate the performance of time-domain equalizer in OFDM system with various channel environments using OMP algorithm compared with other equalization method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.4
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• pp.467-475
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• 2014

In this paper, we introduce a sparse recovery algorithm applied to a radar signal model, based on the compressive sensing(CS), for the formulation of the radar signatures, such as high-resolution range profile(HRRP) and ISAR(Inverse Synthetic Aperture Radar) image. When there exits missing data in observed RCS data samples, we cannot obtain correct high-resolution radar signatures with the traditional IDFT(Inverse Discrete Fourier Transform) method. However, high-resolution radar signatures using the sparse recovery algorithm can be successfully recovered in the presence of data missing and qualities of the recovered radar signatures are nearly comparable to those of radar signatures using a complete RCS data without missing data. Therefore, the results show that the sparse recovery algorithm rather than the DFT method can be suitably applied for the reconstruction of high-resolution radar signatures, although we collect incomplete RCS data due to unwanted interferences or jamming signals.

• Journal of the Korea Institute of Building Construction
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• v.20 no.1
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• pp.11-18
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• 2020

Carbon nanotubes are used in various industries with their excellent mechanical properties and electrical conductivity. In the construction industry, research is being conducted to give self-sensing capabilities to structures, but the results of experiments vary among researchers, and the analysis is insufficient. Therefore, in this study, the hydration and electrical properties of MWCNT-added cement pastes were measured. The electrical resistance values of hydration heat, porosity, Rietveld quantitative analysis, compressive strength, and distance were measured.. The heat resistance, porosity, Rietvelt quantitative analysis, compressive strength and distance were measured according to electrical resistance. Experimental results showed that the heat of hydration decreased with increasing MWCNT. XRD Rietveld quantitative analysis showed that there was no significant difference in the amount of hydration products with increasing addition rate of MWCNT. As a result of SEM analysis, the MWCNT is agglomerated by van der Waals forces, and this area is considered to be caused by voids and weak areas. The electrical resistance value decreases as the addition rate is increased, and thus may play a role for magnetic sensing in the future.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.8
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• pp.636-645
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• 2017

A scanning radar is exploited widely such as for ground surveillance, disaster rescue, and etc. However, the range resolution is limited by transmitted bandwidth and cross-range resolution is limited by beam width. In this paper, we propose a method for super-resolution radar imaging. If the distribution of reflectivity is sparse, the distribution is called sparse signal. That is, the problem could be formulated as compressive sensing problem. In this paper, 2D super-resolution radar image is generated via reweighted ${\ell}_1-Minimization$. In the simulation results, we compared the images obtained by the proposed method with those of the conventional Orthogonal Matching Pursuit(OMP) and Synthetic Aperture Radar(SAR).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1452-1459
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• 2016

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 $4{\times}4$ Hadamard transform matrix provides superior performance in block size 4.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.3
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• pp.233-243
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• 2017

This paper proposes a structure of direct-printed flexible tactile-sensor. These flexible tactile sensors are based on pressure-sensing materials that allow pressure to be measured according to resistance change that in turn results from changes in material size because of compressive force. The sensing material consists of a mixture of multi walled carbon nanotubes (MWCNTs) and TangoPlus, which gives it flexibility and elasticity. The tactile sensors used in this study were designed in the form of array structures composed of many lines so that single pressure points can be measured. To evaluate the performance of the flexible tactile sensor, we used specially designed signal-processing electronics and tactile sensors to experimentally verify the sensors' linearity. To test object grasp, tactile sensors were attached to the surface of the fingers of grippers with three degrees of freedom to measure the pressure changes that occur during object grasp. The results of these experiments indicate that the flexible tactile sensor-based robotic gripper can grasp objects and hold them in a stable manner.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.699-712
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• 2016

Recently, greedy algorithm has received much attention as a cost-effective means to reconstruct the sparse signals from compressed measurements. Much of previous work has focused on the investigation of a single candidate to identify the support (index set of nonzero elements) of the sparse signals. Well-known drawback of the greedy approach is that the chosen candidate is often not the optimal solution due to the myopic decision in each iteration. In this paper, we propose a tree search based sparse signal recovery algorithm referred to as the tree search matching pursuit (TSMP). Two key ingredients of the proposed TSMP algorithm to control the computational complexity are the pre-selection to put a restriction on columns of the sensing matrix to be investigated and the tree pruning to eliminate unpromising paths from the search tree. In numerical simulations of Internet of Things (IoT) environments, it is shown that TSMP outperforms conventional schemes by a large margin.

• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.954-963
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• 2012

As a greedy algorithm reconstructing the sparse signal from underdetermined system, orthogonal matching pursuit (OMP) algorithm has received much attention. In this paper, we multiple candidate matching pursuit (MuCaMP), which builds up candidate support set in every iteration and uses the minimum residual at last iteration. Using the restricted isometry property (RIP), we derive the sufficient condition for MuCaMP to recover the sparse signal exactly. The MuCaMP guarantees to reconstruct the K-sparse signal when the sensing matrix satisfies the RIP constant ${\delta}_{N+K}<\frac{\sqrt{N}}{\sqrt{K}+3\sqrt{N}}$. In addition, we show a recovery performance both noiseless and noisy measurements.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.6
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• pp.501-508
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• 2007

This paper presents the feasibility of using electromechanical impedance based active sensing technique for nondestructive strength gain monitoring of early-age concrete by employing piezoelectric lead-zirconate-titanate (PZT) patches on concrete surface. The strength development of early age concrete is actively monitored by performing a series of experiments on concrete specimens under moist curing condition. The electrical admittance signatures are acquired for five different curing ages and compared with each other. The resonant frequency shifts of PZT patches with increasing days is observed which is on account of additional stiffening due to strength gain of concrete during curing and level of stiffening being related to strength obtained from compression tests on companion cylinder specimens. The proposed approach is found to be suitable for monitoring the development of compressive strength in early-age concrete. It is also observed in this study that root mean square deviation (RMSD) in admittance signatures of the PZT patches can also be used as an indicator of concrete strength development.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.6
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• pp.167-173
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• 2016

Compressed Sensing(CS) is the theory that can recover signals which are sampled below the Nyquist sampling rate to original analog signals. In this paper, we propose the estimation algorithm of ultrasonic attenuation coefficients in the frequency domain using CS. While most estimation algorithms transform the time-domain signals into the frequency-domain using the Fourier transform, the proposed method directly utilize the spectral information in the recovery process by the basis matrix without the completely recovered signals in the time domain. We apply three transform bases for sparsifying and estimate the attenuation coefficients using the Centroid Downshift method with Dual-reference diffraction compensation technique. The estimation accuracy and execution time are compared for each basis matrix. Computer simulation results show that the DCT basis matrix exhibits less than 0.35% estimation error for the compressive ratio of 50% and about 6% average error for the compressive ratio of 70%. The proposed method which directly extracts frequency information from the CS signals can be extended to estimating for other ultrasonic parameters in the Quantitative Ultrasound (QUS) Analysis.