• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.20-33
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• 2015

Spectrum sensing is a key component of cognitive radio. The prediction of the primary user status in a low signal-to-noise ratio is an important factor in spectrum sensing. However, because of noise uncertainty, secondary users have difficulty distinguishing between the primary signal and an unauthorized signal when an unauthorized user exists in a cognitive radio network. To resolve the sensitivity to the noise uncertainty problem, we propose an entropy-based spectrum sensing scheme to detect the primary signal accurately in the presence of an unauthorized signal. The proposed spectrum sensing uses the conditional entropy between the primary signal and the unauthorized signal. The ability to detect the primary signal is thus robust against noise uncertainty, which leads to superior sensing performance in a low signal-to-noise ratio. Simulation results show that the proposed spectrum sensing scheme outperforms the conventional entropy-based spectrum sensing schemes in terms of the primary user detection probability.

• Transactions of the Society of Information Storage Systems
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• v.1 no.1
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• pp.48-52
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• 2005

The research topic of super-RENS technology is shifting from the signal intensity (CNR; Carrier to Noise Ratio) to the signal uniformity (Jitter or bER). To achieve an uniform signal characteristics, it is important to reduce signal fluctuation in a super-RENS disc. In this study, we investigated the relation between signal fluctuation and low frequency noise (LFN), and analyzed LFN increase in recording and readout processes. It was found that signal fluctuation had a close relationship with the LFN. Also, it was found that the recorded mark shape such a bubble type and high readout power increased the LFN in recording and readout process of a super-RENS disc. So, using non-bubble type recording material and low super-resolution readout material, we markedly improved the LFN in a super-RENS disc.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.8
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• pp.1332-1338
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• 1997

In the case of the transfer function for the secondary path is dependent on time, the on-line method which can model it is continuously must be applied to the active noise control technique. And the adaptive random noise technique among the on-line methods is effective in the narrow-band control. In this method, the signal to noise ratio between random noise for modeling and primary noise is low. Therefore, the estimations of transfer function will be prone to inaccuracies and the convergence time will be too long. Such imperfections will have an influence upon the performance of an active noise controller. In this study, t enhance the signal to noise ratio, the on-line method that is combined the conventional adaptive random noise technique and the adaptive line enhancer, is proposed. By using proposed on-line method, a rigorous system identification and control of primary noise have been implemented.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.5
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• pp.38-43
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• 1996

Windowing routines have as their purpose the reduction of the sidelobes of a spectral output of the FFT or DFT routines. Windowing routines accomplish this by forcing the beginning and end of any sequence to approach each other in value. Since they must work with any sequence they force the beginning and ending samples near zero. To make up for this reduction in power, windowing routines give extra weight to the values near the middle of the sequence. The difference between windows is the way in which they transition from the low weights near the edges to the higher weights neqr the middle of the sequence. Signal-to-noise ratio(SNR) can be determined by the ratio of the output noisy signal variance to the input noisy signal variance of a window. Standard deviation of noise is reduced by windowing. Thus, the windowing operation improved the SNR of the noisy signal. This paper shows a performance estimation of windowing on a single tone with added Gaussian noise and uniform noise.

• 한국가시화정보학회:학술대회논문집
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• 2001.12a
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• pp.123-137
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• 2001

PIV (particle image velocimetry) systems use a camera to take snapshots of particles carried by a fluid at some precise instants. Signal processing methods are then used to compute the flow velocity field. In this paper, the design of the camera objective (optics) is addressed. The optimization is done in order to maximize the signal-to-noise ratio of in-focus particles. Four different kinds of noise are considered: photon shot noise, thermal and read noise, background glow shot noise, and noise made by the other particles. A semi-empirical model for the lens aberrations of a two-doublet objective is first addressed, since further, it is shown that lens aberrations (low f-value $f_{\#}$) should be used instead of the Fraunhofer diffraction (high f-value) for the fitting of the particle image size with the pixel size. Other important conclusions of the paper include the expression of optimum values for the magnification M, for the exposure period $\tau$ and for the pixel size $\xi$.

• Current Optics and Photonics
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• v.5 no.3
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• pp.213-219
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• 2021

We describe a single-channel rubidium (Rb) radio-frequency atomic magnetometer (RFAM) as a receiver that takes magnetic signal resonating with Zeeman splitting of the ground state of Rb. We optimize the performance of the RFAM by recording the response signal and signal-to-noise ratio (SNR) in various parameters and obtain a noise level of 159 $fT{\sqrt{Hz}}$ around 30 kHz. When a resonant radiofrequency magnetic field with a peak amplitude of 8.0 nT is applied, the bandwidth and signal-to-noise ratio are about 650 Hz and 88 dB, respectively. It is a good agreement that RFAM using alkali atoms is suitable for receiving signals in the very low frequency (VLF) carrier band, ranging from 3 kHz to 30 kHz. This study shows the new capabilities of the RFAM in communications applications based on magnetic signals with the VLF carrier band. Such communication can be expected to expand the communication space by overcoming obstacles through the high magnetic sensitive RFAM.

• The Journal of the Acoustical Society of Korea
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• v.41 no.5
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• pp.507-517
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• 2022

The PhotoAcoustic Microscopy (PAM) has been proved to be a useful tool for biological and medical applications due to its high spatial and contrast resolution. PAM is based on transmission of laser pulses and reception of PA signals. Since the strength of PA signals is generally low, not only are high-performance optical and acoustic modules required, but high-performance electronics for imaging are also particularly needed for high-quality PAM imaging. Most PAM systems are implemented with a combination of several pieces of equipment commercially available to receive, amplify, enhance, and digitize PA signals. To this end, PAM systems are inevitably bulky and not optimal because general purpose equipment is used. This paper reports a PA signal receiving system recently developed to attain the capability of improved Signal to Noise Ratio (SNR) and Contrast to Noise Ratio (CNR) of PAM images; the main module of this system is a low noise, wideband signal receiver that consists of two low-noise amplifiers, two variable gain amplifiers, analog filters, an Analog to Digital Converter (ADC), and control logic. From phantom imaging experiments, it was found that the developed system can improve SNR by 6.7 dB and CNR by 3 dB, compared to a combination of several pieces of commercially available equipment.

• Journal of radiological science and technology
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• v.30 no.4
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• pp.329-334
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• 2007

This paper is for investigation of the noise reduction effect all 20 filters by combining Low Pass Filter(LPF) 5 kinds, High Pass Filter(HPF) 4 kinds, Median Filter(MF) 11 kinds. Noise is added to reduce noise and minimize the quality degradation in medical imaging system. We also compared Peak Signal to Noise Ratio(PSNR), Mean Square Error(MSE) for all the combinations of different filters. As a result, noise decrease appeared in the LPF3*3#1 + HPF3*3#1 + Vertical3*1 of highest filter. We confirmed noise reduction effect by applying the proposed filter combination in many fields of medical imaging applications.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.19-25
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• 2023

In this paper, we propose a method for improving raw images captured in a low light condition based on deep learning considering the image signal processing. In the case of a smart phone camera, compared to a DSLR camera, the size of a lens or sensor is limited, so the noise increases and the reduces the quality of images in low light conditions. Existing deep learning-based low-light image processing methods create unnatural images in some cases since they do not consider the lens shading effect and white balance, which are major factors in the image signal processing. In this paper, pixel distances from the image center and channel average values are used to consider the lens shading effect and white balance with a deep learning model. Experiments with low-light images taken with a smart phone demonstrate that the proposed method achieves a higher peak signal to noise ratio and structural similarity index measure than the existing method by creating high-quality low-light images.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.4
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• pp.358-365
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• 2005

In induction machine drive without a speed sensor, the estimation of the motor flux and speed often becomes deteriorated at low speeds with low back EMF. Our analysis shows that, in addition to the state resistance variation, the estimated value of field orientation angle is often corrupted by accumulative errors from the integration of voltage variables at motor terminals that have low signal/noise ratio at low frequencies. A repetitive loop path of integration in the feedback can amplify this type of error, thus speeding up the degradation process. The control system runs into information starvation due to the loss of correct field orientation. The machine's spiral vectors are controlled only in a reduced dimension in this situation. A novel control scheme is developed to improve the control performance of motor's current, torque and speed at low frequencies. The scheme gains a full-dimensional vector control and is less sensitive to the combined effect of the error sources at the low frequencies. Experimental tests demonstrate promising performances are achievable even below 0.5 Hz.