• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.316-319
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• 1998

RPWM(Random Pulse Width Modulation) is a switching technique to spread the voltage and current harmonics on the wide frequency area. Using randomly changed switching frequency of the inverter, the power spectrum of the electromagnetic acoustic noise cab be spread to the wide-band area. The wide-band noise is much more comfortable and less annoying than the narrow-band one. So RPWM have been attracting an interest as an excellent method for the reduction of acoustic noise on the inverter drive system. In this paper a new RPPWM (Random Position PWM) is proposed and implemented. Each of three pulses is located randomly in each switching interval. Along with the randomization of PWM pulses, the space vector modulation is executed in the C167 microcontroller also. The experimental results show that the voltage and current harmonics were spread to wide band area and that the audible switching noise was reduced by proposed RPPWM method.

• The Journal of the Acoustical Society of Korea
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• v.35 no.2
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• pp.102-109
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• 2016

This paper proposes a noise suppression method through SNR (Singal-to Noise Ratio) estimation in the two microphone array environment of close spacing. The conventional method uses a noise suppression method for a gain function obtained through the SNR estimation based on coherence function from full band. However, this method cause performance decreased by the noise damage that affects all the feature vector component. So, we propose a noise suppression method that allocates a frequency domain signal into N constant multi frequency band and each frequency band gets a gain function through SNR estimation based on coherence function. Performance evaluation of the proposed method is shown by comparison with PESQ (Perceptual Evaluation of Speech Quality) value which is an objective quality evaluation method provided by the ITU-T (International Telecommunications Union Telecommunication).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.5
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• pp.640-645
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• 2012

DC-DC converter and DC-AC inverter in a hybrid electric vehicle (HEV) generate the switching noise. It may be generated by the reverse recovery operation of the power diode in the switching circuit of the converter or the inverter. The shape of the reverse recovery region may be determined by both reverse time and recovery time in the diode. So, in this paper, the frequency spectrum of switching noise was estimated by the shape of the reverse recovery region and compared with the measured results. It shows that the meaningful region of the frequency spectrum is directly related with the reverse time.

• Proceedings of the KIEE Conference
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• 1999.07a
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• pp.465-467
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• 1999

The data transmission system in MAGLEV is required a high quality and high speed for a train safety and reliability driving. In the transmission channel between a vehicle and a ground-site, Gaussian noise is negligible, but impulse noise from the chopper controlled propulsoin unit and the Power supplying device is very severe. The transmission channel must be protected from these noise. In this paper, we propose a DSSS (direct-sequence spread spectrum) modulation as a new data transmission technique in the railway and analyze this data transmission characteristics.

• The Journal of the Acoustical Society of Korea
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• v.28 no.7
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• pp.680-685
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• 2009

In this paper, we propose a efficient noise power estimation technique for an integrated acoustic echo and noise suppression system in a frequency domain. The proposed method uses speech absence probability (SAP) derived from the microphone input signal as the smoothing parameter updating noise power to reduce the noise power estimation error resulted from the distortions in the unified structure where the noise suppression (NS) operation is placed after the acoustic echo suppression (AES) algorithm. Therefore, in the proposed approach, the smoothing parameter based on SAP derived from the input signal instead of echo-suppressed signal should stop updating noise power estimates during the distorted noise spectrum periods. The performance of the proposed algorithm is evaluated by the objective test under various environments and yields better results compared with the conventional scheme.

• ETRI Journal
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• v.39 no.1
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• pp.87-96
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• 2017

Ultrasonic surgical devices are routinely used for surgical procedures. The incision and coagulation of tissue generate a temperature of $40^{\circ}C-150^{\circ}C$ and depend on the controllable output power level of the surgical device. Recently, research on the classification of grasped tissues to automatically control the power level was published. However, this research did not consider the specific characteristics of the surgical device, tissue denaturalization, and so on. Therefore, this research proposes a robust algorithm that simulates noise to resemble real situations and classifies tissue using conventional classifier algorithms. In this research, the bioimpedance spectrum for six tissues (liver, large intestine, kidney, lung, muscle, and fat) is measured, and five classifier algorithms are used. A signal-to-noise ratio of additive white Gaussian noise diversifies the testing sets, and as a result, each classifier's performance exhibits a difference. The k-nearest neighbors algorithm shows the highest classification rate of 92.09% (p < 0.01) and a standard deviation of 1.92%, which confirms high reproducibility.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.175-179
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• 2007

To existing method which uses energy variation and spectrum deviation to detect the underwater transient signal is useful to detect white noise environment, but it is not useful to do colored noise environment. To improve capacity of detecting the underwater transient signal both in white noise environment and colored noise environment, this study takes advantage of Double Density Discrete Wavelet Transform and CFAR Power-Law.

• Proceedings of the KIPE Conference
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• 2003.07a
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• pp.308-312
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• 2003

The objective of this paper is to investigate the power spectrum of a three-phase and a two-phase RCD (Random Pulse Centered Displacement) PWM scheme. The two-phase or three-phase pulses of RCD-PWM scheme are mutually center-aligned as in SVM(Space Vector Modulation), but the common pulse center is displaced randomly from the middle of the period. To verify the validity of the proposed two-phase RCD-PWM scheme, the power spectra of the output voltage, the d.c link current in the inverter drives and the radiated acoustic noise are experimentally investigated. And, the performance of the proposed two-phase RCD-PWM scheme was compared and discussed with the conventional three-phase RCD-PWM scheme.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.841-845
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• 1991

There are Carrier Current Communication or Power line Carrier (PLC) Communication conducted data exchange using power line Which is installed existing indoor. Power line is possible to construct data link economically, on the other hand, have an inferior transmission environment such as irregular noise and severe level variation. The purpose of this paper is to present transmission possibility for PLC using spread spectrum technique. In the initial synchronization, established computer simulation for the S/N in relation to PN code generator. By using this result, construct the prototype SS system and then experiment the transmission characteristics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1489-1503
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• 2018

Spectrum reuse has attracted much concern of researchers and scientists, however, the dynamic spectrum access is challenging, since an individual secondary user usually just has limited sensing abilities. One key insight is that spectrum usage forecasting among secondary users, this inspiration enables users to obtain more informed spectrum opportunities. Therefore, spectrum usage forecasting is vital to cognitive radio networks (CRNs). With this insight, a spectrum usage forecasting model for the occurrence of primary users prediction is derived in this paper. The proposed model is based on auto regressive enhanced primary user emergence reasoning (AR-PUER), which combines linear prediction and primary user emergence reasoning. Historical samples are selected to train the spectrum usage forecasting model in order to capture the current distinction pattern of primary users. The proposed scheme does not require the knowledge of signal or of noise power. To verify the performance of proposed spectrum usage forecasting model, we apply it to the data during the past two months, and then compare it with some other sensing techniques. The simulation results demonstrate that the spectrum usage forecasting model is effective and generates the most accurate prediction of primary users occasion in several cases.