• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9C
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• pp.877-886
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• 2005

Various frame recovery algorithms have been suggested to overcome the communication quality degradation problem due to Internet-typical impairments on Voice over IP(VoIP) communications. In this paper, we propose a new receiver-based recovery method which is able to enhance recovered speech quality with almost free computational cost and without an additional increment of delay and bandwidth consumption. Most conventional recovery algorithms try to recover the lost or erroneous speech frames by reconstructing missing coefficients or speech signal during speech decoding process. Thus they eventually need to modify the decoder software. The proposed frame recovery algorithm tries to reconstruct the missing frame itself, and does not require the computational burden of modifying the decoder. In the proposed scheme, the Vector Quantization(VQ) codebook indices of the erased frame are directly estimated by referring the pre-computed VQ Codebook Index Interpolation Tables(VCIIT) using the VQ indices from the adjacent(previous and next) frames. We applied the proposed scheme to the ITU-T G.723.1 speech coder and found that it improved reconstructed speech quality and outperforms conventional G.723.1 loss recovery algorithm. Moreover, the suggested simple scheme can be easily applicable to practical VoIP systems because it requires a very small amount of additional computational cost and memory space.

• Korean Journal of Optics and Photonics
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• v.16 no.1
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• pp.21-26
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• 2005

10 GHz clock recovery from 40 Gbit/s optical time-division-multiplexed(OTDM) signal pulses was experimentally demonstrated using an optical phase lock loop based on a terahertz optical asymmetric demultiplexer(TOAD) with a local-reference-oscillator-free electronic feedback circuit. The 10 GHz clock was successfully extracted from 40 Gbit/s signals. The SNR of the time-extracted 10 GHz RF signal to the side components was larger than 40 dB. Also we performed numerical simulation about the extraction process of phase information in TOAD. The lock-in frequency range of the clock recovery is found to be 10 kHz.

• 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.

• Investigative Magnetic Resonance Imaging
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• v.25 no.3
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• pp.197-200
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• 2021

Ramsay Hunt syndrome (RHS) is a disease caused by varicella-zoster virus (VZV) infection that can be diagnosed through clinical symptoms with or without imaging evaluations. The typical features of RHS on imaging evaluation include signal changes and enhancement in the internal auditory canal (IAC) nerves, and the labyrinthine segment of cranial nerve VII (CN VII) and cranial nerve VIII (CN VIII). In some patients, inner ear structure (cochlear and vestibular apparatus) is involved in RHS. Neurologic complications, such as encephalitis and meningitis, are rare in RHS, but are known to occur. Therefore, magnetic resonance imaging (MRI) is necessary to detect both abnormal signal intensity in the IAC, CN VII, CN VIII, inner and ear structure, and CNS complications. We report an RHS patient with CN VII, VIII, and leptomeningeal enhancement within the cerebellar folia on 10-min delayed, contrast-enhanced (CE), three-dimensional fluid-attenuated inversion recovery (3D-FLAIR) imaging.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.61-63
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• 2010

Recent work in compressed sensing theory shows that m${\times}$n independent and identically distributed sensing matrices 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 L1 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 L1 minimization via support recovery.

• Journal of electromagnetic engineering and science
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• v.11 no.4
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• pp.250-256
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• 2011

This paper applies a compressed algorithm to improve the spectrum sensing performance of cognitive radio technology. At the fusion center, the recovery error in the analog to information converter (AIC) when reconstructing the transmit signal from the received time-discrete signal causes degradation of the detection performance. Therefore, we propose a subspace pursuit (SP) algorithm to reduce the recovery error and thereby enhance the detection performance. In this study, we employ a wide-band, low SNR, distributed compressed sensing regime to analyze and evaluate the proposed approach. Simulations are provided to demonstrate the performance of the proposed algorithm.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.652-654
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• 2003

Embedded cost pricing is easy to be applied in the calculation of transmission cost and guarantees perfect recovery of revenue requirement. However, it caused in equity of cost distribution in the restructured electrical market. Though, marginal cost pricing has been studied to be applied to economic signal of members. But it has the cumbersome processes of the revenue reconciliation. This paper presents a new recovery of revenue requirement method that is satisfied with economic signal, using MLF.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.11a
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• pp.1-3
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• 2015

In this paper, we propose a sparse signal reconstruction method referred to as the matching pursuit with a pruning-based tree search (PTS-MP). Two key ingredients of PTS-MP 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 our simulations, we confirm that PTS-MP is effective in recovering sparse signals and outperforms conventional sparse recovery algorithms.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2115-2121
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• 2009

This paper proposes the new reclosing scheme considering the recovery time of SFCL in distribution systems which is based on variable dead time control. The main idea is that it uses the carrier signal to distinguish whether the fault is instantaneous or permanent after tripping the line by recloser. The system and SFCL is modeled by using Electromagnetic Transient Program(EMTP) and the validity of the reclosing scheme presented in this paper is analyzed according to the fault resistance, the recovery time of SFCL and the fault clearing time.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.1
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• pp.10-14
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• 1987

Considering transition gating of the input unipolar NRZ signal, the equivalent linear time-invariant model has been derived for the PLL in the timing clock recovery circuits. The magnitude of the alignment and accumulated jitter has been found along a chain of repeaters. For the timing recovery circuit of 90 Mbps optical communication system, the computer simulation shows that, for the first stage of the chain, the alignment jiter and the accumulated jitter are of -5.1766 dB and for the 7-th stage, the alignment jitter and accumulated jitter have the value of -1.0193dB, 4.9053 dB respectively.