• 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.

• Journal of Communications and Networks
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• v.16 no.6
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• pp.583-591
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• 2014

In wireless communications, knowledge of the signal-to-noise ratio is required in diverse communication applications. In this paper, we derive the variance of the maximum likelihood estimator in the data-aided and non-data-aided schemes for determining the optimal shrinkage factor. The shrinkage factor is usually the constant that is multiplied by the unbiased estimate and it increases the bias slightly while considerably decreasing the variance so that the overall mean squared error decreases. The closed-form biased estimators for binary-phase-shift-keying and quadrature phase-shift-keying systems are then obtained. Simulation results show that the mean squared error of the proposed method is lower than that of the maximum likelihood method for low and moderate signal-to-noise ratio conditions.

• Journal of the Korean Data and Information Science Society
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• v.12 no.1
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• pp.11-18
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• 2001

Taguchi parameter design is an approach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used signal-to-noise(SN) ratio to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Many statisticians criticize the Taguchi techniques of analysis, particularly those based on SN ratio. In this paper we propose a substantially simpler optimization procedure for parameter design without resorting to SN ratio.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.748-764
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• 2019

In order to deal with the filtering delay problem of least mean square adaptive filter noise reduction algorithm and music noise problem of spectral subtraction algorithm during the speech signal processing, we combine these two algorithms and propose one novel noise reduction method, showing a strong performance on par or even better than state of the art methods. We first use the least mean square algorithm to reduce the average intensity of noise, and then add spectral subtraction algorithm to reduce remaining noise again. Experiments prove that using the spectral subtraction again after the least mean square adaptive filter algorithm overcomes shortcomings which come from the former two algorithms. Also the novel method increases the signal-to-noise ratio of original speech data and improves the final noise reduction performance.

• Journal of Magnetics
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• v.21 no.3
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• pp.330-339
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• 2016

A magnetic field sensing system with a single primary sensor and multiple reference sensors deployed locally and orthogonally, was proposed for downlink signal reception and interference cancelling for Through-the-Earth Communication (TEC). This paper mathematically analyzes a design optimization process for a search coil magnetometer (SCM), and applies that process to minimize the bandwidth of the primary SCM for TEC signal reception and the volume of reference SCMs for multiple distributions. The primary SCM achieves a 3-dB bandwidth of 7 Hz, a sensitivity threshold of 120 fT/${\surd}$Hz, and a volume of $2.32{\times}10^{-4}m^3$. The entire sensing system volume is as small as $10^{-2}m^3$. Experiments with interference from industrial frequency harmonics demonstrated an average of 36 dB and 18 dB improvements in signal-to-interference ratio and signal-to-interference plus noise ratio, respectively, using multichannel recursive-least-squares algorithm. Thus, the proposed sensing system can reduce the interference effectively and allows reliable downlink signal reception.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.1
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• pp.44-57
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• 2013

In this paper, we propose a femtocell searching technique which can prevent a macrocell UE(user equipment) from losing synchronism to its serving macrocell near closed access femtocells in co-channel deployment due to the leakage of femtocell signals by using a CS(Common Signal). The CS, commonly transmitted by femtocells in a macrocell at the same time, enables the macrocell UEs to be kept synchronized with their serving macrocells since the CINR(Carrier to Interference and Noise Ratio) of base stations in macrocell can be kept high even near closed access femtocells. Also, the CS is designed in such a way that a macrocell UE can recognize the existence of femtocell by using the metric CSCINR(Common Signal Carrier to Interference and Ratio) measured with CS. In addition, the proposed femtocell searching technique can reduce the frequency of femtocell searching trial by using the metric on mobility of a macrocell UE defined in this paper, and the reduction of the frequency of handover trial can be also expected as a byproduct.

• Proceedings of the KSME Conference
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• 2002.08a
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• pp.353-356
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• 2002

Planar laser induced fluorescence(PLIF) has been widely used to obtain two dimensional fuel distribution. Preliminary investigation was performed to measure quantitative air excess ratio distribution in an engine fueled with LPG. It is known that fluorescence signal from acetone as a fluorescent tracer is less sensitive to oxygen quenching than other dopants. Acetone was excited by KrF excimer laser (248nm) and its fluorescence image was acquired by ICCD camera with a cut-of filter to suppress Mie scattering from the laser light. For the purpose of quantifying PLIF signal, an image processing method including the correction of laser sheet beam profile was suggested. Raw images were divided by each intensity of laser energy and profile of laser sheet beam. Inhomogeneous fluorescence images scaled with the reference data, which was taken by a calibration process, were converted to air excess ratio distribution. This investigation showed instantaneous quantitative measurement of planar air excess ratio distribution for gaseous fuel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8C
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• pp.806-815
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• 2006

It is studied to design a low pass filter of the SRC(sample rate converter), which is used to change the sampling rate of digital signals such as in digital modulation and demodulation systems. The larger the conversion ratio of the sample rate becomes, the more signal processing is needed for the filter, which corresponds to the more complexity in circuit realization. Thus it is important to reduce the amount of signal processing for the case of high conversion ratio. In this paper it is presented a design method of a two-stage cascaded FIR filter, which proved to have reduced amount of signal processing in comparison with a conventional single-stage one. The reduction effect of signal processing turned out to be more noticeable for larger value of conversion ratio, for instance, giving down to 72% in complexity for the conversion ratio of 32. It has been shown that the reduction effect is dependent to specific combination of conversion ratios of the cascaded filters. So an exhaustive search has been performed in order to obtain the optimal combination for various values of the total conversion ratio. In this paper every filter is considered to be implemented in the form of a polyphase FIR filter, and its coefficients are determined by use of the Parks-McCllelan algorithm.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1249-1256
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• 2019

In this paper, we propose a new algorithm to remove acoustic feedback and noise in hearing aids. Instead of using the conventional FIR structure, this algorithm is a deep learning algorithm using neural network adaptive prediction filter to improve the feedback and noise reduction performance. The feedback canceller first removes the feedback signal from the microphone signal and then removes the noise using the Wiener filter technique. Noise elimination is to estimate the speech from the speech signal containing noise using the linear prediction model according to the periodicity of the speech signal. In order to ensure stable convergence of two adaptive systems in a loop, coefficient updates of the feedback canceller and noise canceller are separated and converged using the residual error signal generated after the cancellation. In order to verify the performance of the feedback and noise canceller proposed in this study, a simulation program was written and simulated. Experimental results show that the proposed deep learning algorithm improves the signal to feedback ratio(: SFR) of about 10 dB in the feedback canceller and the signal to noise ratio enhancement(: SNRE) of about 3 dB in the noise canceller than the conventional FIR structure.

• ETRI Journal
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• v.31 no.3
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• pp.263-270
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• 2009

This paper investigates linear soft combination schemes for cooperative spectrum sensing in cognitive radio networks. We propose two weight-setting strategies under different basic optimality criteria to improve the overall sensing performance in the network. The corresponding optimal weights are derived, which are determined by the noise power levels and the received primary user signal energies of multiple cooperative secondary users in the network. However, to obtain the instantaneous measurement of these noise power levels and primary user signal energies with high accuracy is extremely challenging. It can even be infeasible in practical implementations under a low signal-to-noise ratio regime. We therefore propose reference data matrices to scavenge the indispensable information of primary user signal energies and noise power levels for setting the proposed combining weights adaptively by keeping records of the most recent spectrum observations. Analyses and simulation results demonstrate that the proposed linear soft combination schemes outperform the conventional maximal ratio combination and equal gain combination schemes and yield significant performance improvements in spectrum sensing.