• Journal of Communications and Networks
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• v.18 no.3
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• pp.439-445
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• 2016

In this paper, we consider subcarrier-index modulation (SIM) for precoded orthogonal frequency division multiplexing (OFDM) with a few activated subcarriers per user and its generalization to multi-carrier multiple access systems. The resulting multiple access is called sparse index multiple access (SIMA). SIMA can be considered as a combination of multi-carrier code division multiple access (MC-CDMA) and SIM. Thus, SIMA is able to exploit a path diversity gain by (random) spreading over multiple carriers as MC-CDMA. To detect multiple users' signals, a low-complexity detection method is proposed by exploiting the notion of compressive sensing (CS). The derived low-complexity detection method is based on the orthogonal matching pursuit (OMP) algorithm, which is one of greedy algorithms used to estimate sparse signals in CS. From simulation results, we can observe that SIMA can perform better than MC-CDMA when the ratio of the number of users to the number of multi-carrier is low.

• Korean Institute of Interior Design Journal
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• no.29
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• pp.220-227
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• 2001

Display and art have different purposes. But they share a common mean, so-called artistic experience. These two formative business that seeks the profit as a commercial design, it has some relationship with art in the aspect of socialization of pursuit of aesthetics. Although the historical status and directivity of display have not been established systemiically yet, and aesthetic expansion of displace is uncertain it would be effective that the present and future of display art is connected with art history in the view of dynamic state of art history. In this thesis, the issues such as what is the relationship between display and art history or whether display can be mentioned as a formative art were analyzed by matching them with the trends in art history like naturalism, high tech, minimalists and so on. Modern display is a commercial design that can be developed in various ways and that is related to the as development of art history.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.399-409
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• 2019

Three-dimensional (3D) human pose reconstruction from single-view image is a difficult and challenging topic. Existing approaches mostly process frame-by-frame independently while inter-frames are highly correlated in a sequence. In contrast, we introduce a novel spatial-temporal 3D human pose reconstruction framework that leverages both intra and inter-frame relationships in consecutive 2D pose sequences. Orthogonal matching pursuit (OMP) algorithm, pre-trained pose-angle limits and temporal models have been implemented. Several quantitative comparisons between our proposed framework and recent works have been studied on CMU motion capture dataset and Vietnamese traditional dance sequences. Our framework outperforms others by 10% lower of Euclidean reconstruction error and more robust against Gaussian noise. Additionally, it is also important to mention that our reconstructed 3D pose sequences are more natural and smoother than others.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.410-421
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• 2019

Distributed compressed sensing (DCS) states that we can recover the sparse signals from very few linear measurements. Various studies about DCS have been carried out recently. In many practical applications, there is no prior information except for standard sparsity on signals. The typical example is the sparse signals have block-sparse structures whose non-zero coefficients occurring in clusters, while the cluster pattern is usually unavailable as the prior information. To discuss this issue, a new algorithm, called backtracking-based adaptive orthogonal matching pursuit for block distributed compressed sensing (DCSBBAOMP), is proposed. In contrast to existing block methods which consider the single-channel signal reconstruction, the DCSBBAOMP resorts to the multi-channel signals reconstruction. Moreover, this algorithm is an iterative approach, which consists of forward selection and backward removal stages in each iteration. An advantage of this method is that perfect reconstruction performance can be achieved without prior information on the block-sparsity structure. Numerical experiments are provided to illustrate the desirable performance of the proposed method.

• Journal of Power Electronics
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• v.19 no.2
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• pp.443-453
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• 2019

As the core component of transmission systems, converters are very prone to failure. To improve the accuracy of fault diagnosis for wind power converters, a fault feature extraction method combined with a wavelet transform and compressed sensing theory is proposed. In addition, an improved AdaBoost-SVM is used to diagnose wind power converters. The three-phase output current signal is selected as the research object and is processed by the wavelet transform to reduce the signal noise. The wavelet approximation coefficients are dimensionality reduced to obtain measurement signals based on the theory of compressive sensing. A sparse vector is obtained by the orthogonal matching pursuit algorithm, and then the fault feature vector is extracted. The fault feature vectors are input to the improved AdaBoost-SVM classifier to realize fault diagnosis. Simulation results show that this method can effectively realize the fault diagnosis of the power transistors in converters and improve the precision of fault diagnosis.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.3
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• pp.315-321
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• 2023

In this paper, we propose an algorithm that jointly estimates the location and velocity of a near-field moving target in a pulse radar system. The proposed algorithm estimates the location and velocity corresponding to the outcome of orthogonal matching pursuit (OMP) in a 4-dimensional (4D) location-velocity space. To address the high computational complexity of 4D parameter joint estimation, we propose an algorithm that iteratively estimates the target's 2D location and velocity sequentially. Through simulations, we analyze the estimation performance and verify the computational efficiency of the proposed algorithm.

• The Research Journal of the Costume Culture
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• v.19 no.6
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• pp.1163-1176
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• 2011

The purposes of this study was to identify characteristics of total coordination in the pursuit fashion sensibility among women their 20's. A self-administered questionnaire was used for data collection from 410 women in their 20's. Data collection was conducted Aug. 5 to Aug. 15, 2009. Most women emphasized on clothing for total coordination and utilized clothing color and style as a selection criteria. They tried to match makeup and clothing, and spent more time considering makeup, hair styles, and fashion accessaries than clothing for their total coordination. Factors of fashion sensibility included luxury and fashion, casualness and ethnicity, modernity, sociality, activity, and sexual attractiveness and women were segmented into fashionably sensible intermediate, low, and high groups according to their fashion sensibility. The fashionably sensible intermediate group predominantly encompassed women who were unmarried or in their late 20's, unemployed, highly educated, or of low economic status, preferred to mixing and matching colors, and who utilized their individuality or makeup color for total coordination. The fashionably sensible low group encompassed homemakers, in their early 20's, high school graduates or university students, who utilized their clothing or hair color within their total coordination criteria. The fashionably sensible high group encompassed unmarried career women in their mid 20's or of high economic status, who spent much money on their clothing, makeup, hair styles, and fashion accessaries, who preferred achromatic, warm or cool colors, and utilized their individuality or fashion color.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1557-1564
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• 2014

In this paper, we propose a signal detection technique based on the parallel orthogonal matching pursuit (POMP) is proposed for generalized shift space keying (GSSK) systems, which is a modified version of the orthogonal matching pursuit (OMP) that is widely used as a greedy algorithm for sparse signal recovery. The signal recovery problem in the GSSK systems is similar to that in the compressed sensing (CS). In the proposed POMP technique, multiple indexes which have the maximum correlation between the received signal and the channel matrix are selected at the first iteration, while a single index is selected in the OMP algorithm. Finally, the index yielding the minimum residual between the received signal and the M recovered signals is selected as an estimate of the original transmitted signal. POMP with Quantization (POMP-Q) is also proposed, which combines the POMP technique with the signal quantization at each iteration. The proposed POMP technique induces the computational complexity M times, compared with the OMP, but the performance of the signal recovery significantly outperform the conventional OMP algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.134-140
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• 2011

Recent work in compressed sensing theory shows that $M{\times}N$ independent and identically distributed sensing matrix whose entries are drawn independently from certain probability distributions guarantee exact recovery of a sparse signal with high probability even if $M{\ll}N$. In particular, it is well understood that the $L_1$-minimization algorithm is able to recover sparse signals from incomplete measurements. In this paper, we propose a novel sparse signal reconstruction method that is based on the reweighted $L_1$-minimization via support detection.