• Journal of Sensor Science and Technology
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• v.12 no.4
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• pp.191-197
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• 2003

Due to explosive increase of internet usage, broadband data transmission using optical fibers is broadly used. In order to decrease distortion during long distance transmission, the optical signal need to be restored, typically, by converting the optical signal into the electrical signal. The optical signal is converted into the electrical signal using a photo-diode, and then a clock-and-recovery (CDR) circuit is used to recover the clock and retime the data. In this study, a clock-and-data recovery circuit has been designed using a standard 1.8 V $0.18\;{\mu}m$ CMOS process. With this CDR circuit, the improved phase detector and charge pump have been utilized. Also, by using a ring oscillator, the CDR circuit can recover clock and data from broadband multi-rate data ranging between 750 Mb/s and 2.85 Gb/s.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.6
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• pp.628-630
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• 2016

Compressive sensing can recover an original sparse signal from a few measurements. Its performance is affected by the number of non-zero elements in the signal. The knowledge of partial locations of non-zero elements can improve the recovery performance. In this paper, we apply the partial location knowledge to the multipath matching pursuit. The numerical results show it improves the signal recovery performance and the channel estimation performance in the ITU-VB channel.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.461-484
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• 2021

Compressed sensing in image reconstruction has attracted attention and many studies are proposed. As we know, adding prior knowledge about the distribution of the support on the original signal to CS can improve the quality of reconstruction. However, it is still difficult for a recovery framework adjusts its strategy for exploiting the prior knowledge efficiently according to the current estimated signals in serial iterations. With the theory of information geometry, we propose an adaptive strategy based on the current estimated signal in each iteration of the recovery. We also improve the performance of existing algorithms through the adaptive strategy for exploiting the prior knowledge according to the current estimated signal. Simulations are presented to validate the results. In the end, we also show the application of the model in the image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1618-1637
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• 2018

By means of compressive sensing (CS) technique, this paper considers the collection of sensor data with spatiotemporal correlations in wireless sensor networks (WSNs). In energy-constrained WSNs, one-dimensional CS methods need a lot of data transmissions since they are less applicable in fully exploiting the spatiotemporal correlations, while the Kronecker CS (KCS) methods suffer performance degradations when the signal dimension increases. In this paper, an appropriate sensing matrix as well as an efficient sensing method is proposed to further reduce the data transmissions without the loss of the recovery performance. Different matrices for the temporal signal of each sensor node are separately designed. The corresponding energy-efficient data gathering method is presented, which only transmitting a subset of sensor readings to recover data of the entire WSN. Theoretical analysis indicates that the sensing structure could have the relatively small mutual coherence according to the selection of matrix. Compared with the existing spatiotemporal CS (CS-ST) method, the simulation results show that the proposed efficient measurement method could reduce data transmissions by about 25% with the similar recovery performance. In addition, compared with the conventional KCS method, for 95% successful recovery, the proposed sensing structure could improve the recovery performance by about 20%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5103-5115
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• 2015

In radar imaging, a target is usually consisted of a few strong scatterers which are sparsely distributed. In this paper, an improved sparse signal recovery algorithm based on smoothed l₀ (SL0) norm method is proposed to achieve high resolution ISAR imaging with limited pulse numbers. Firstly, one new smoothed function is proposed to approximate the l₀ norm to measure the sparsity. Then a single loop step is used instead of two loop layers in SL0 method which increases the searching density of variable parameter to ensure the recovery accuracy without increasing computation amount, the cost function is undated in every loop for the next loop until the termination is satisfied. Finally, the new set of solution is projected into the feasible set. Simulation results show that the proposed algorithm is superior to the several popular methods both in terms of the reconstruction performance and computation time. Real data ISAR imaging obtained by the proposed algorithm is competitive to several other methods.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.222-227
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• 2022

The purpose of this study was to investigate changes in heart rate according to recovery methods after circuit weight training exercise. Fourteen men in their twenties were selected as subjects, and three sets of circuit weight training were performed by cycling six sports, and two recovery conditions (dynamic and static) were performed immediately after exercise. Changes in heart rate did not have an interactive effect according to recovery method and time, and both conditions showed significant changes between sets 1 and 2, and between sets 3 and after recovery. In this study, the high heart rate of 2 sets and 3 sets was seen as a result of exercise stimulation, and the low heart rate of 1 set was thought to be due to the decrease in vagus nerve activity rather than the role of catecholamines. On the other hand, the heart rate after 20 minutes of exercise did not show any difference according to the recovery method, which could mean that the recovery process due to the aquatic environment can act more strongly than the process of dynamic recovery and static recovery. It is thought that the characteristics affected the sensory and circulation of the body, and thus the change of the afferent signal and the level of metabolic products generated in the active muscle.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4C
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• pp.371-376
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• 2010

In this paper, we propose a new fast carrier recovery algorithm for high-order QAM systems. The proposed algorithm detects carrier frequency offset from the phase differences among the received symbols directly and combines it with the conventional carrier recovery, so that it is possible to achieve the carrier recovery with wide tracking range and fast acquisition time. Simulation results show that the proposed carrier recovery method reduces acquisition time at large frequency offset and low signal-to-noise ratio (SNR).

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.2
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• pp.95-99
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• 2005

This paper presents an accurate recovery method of the reference clock which is needed for network synchronization in two-way satellite multimedia systems compliant with DVB-RCS specification and which use closed loop method for burst synchronization. In these systems, the remote station transmits TDMA burst via return link. For burst synchronization, it obtains reference clock from program clock reference (PCR) defined by MPEG-2 system specification. The PCR is generated periodically at the hub system by sampling system clock which runs at 27MHz $\pm$ 30ppm. Since the reference clock is recovered by means of digital PLL(DPLL) using imprecise PCR values due to variable random jitter, the recovered clock frequency of remote station doesn't exactly match reference clock of hub station. We propose a robust recovery method of reference clock against random delay jitter The simulation results show that the recovery error is remarkably decreased from 5 clocks to 1 clock of 27MHz relative to the general DPLL recovery 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 Korean Neurosurgical Society
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• v.50 no.3
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• pp.209-215
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• 2011

Objective : The authors investigated the changes of cortical sensorimotor activity in functional MRI (fMRI) and functional recovery in spinal cord injury (SCI) patients who had been treated by bone marrow cell transplantation. Methods : Nineteen patients with SCI were included in this study; ten patients with clinical improvement and nine without. The cortical sensorimotor activations were studied using the proprioceptive stimulation during the fMRI. Results : Diagnostic accuracy of fMRI with neurological improvement was 70.0% and 44.4% for sensitivity and specificity, respectively. Signal activation in the ipsilateral motor cortex in fMRI was commonly observed in the clinically neurological improved group (p-value=0.002). Signal activation in the contralateral temporal lobe and basal ganglia was more commonly found in the neurological unimproved group (p-value<0.001). Signal activation in other locations was not statistically different. Conclusion : In patients with SCI, activation patterns of fMRI between patients with neurologic recovery and those without varied. Such plasticity should be considered in evaluating SCI interventions based on behavioral and neurological measurements.