• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.447-453
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• 2009

This paper introduces the method for detect voices and exact end point at low SNR by maximizing voice energy. Conventional VAD (Voice Activity Detection) algorithm estimates noise level so it tends to detect the end point inaccurately. Moreover, because it uses relatively long analysis range for reflecting temporal change of noise, computing load too high for application. In this paper, the SEM-VAD (Speech Energy Maximization-Voice Activity Detection) method which uses psycho-acoustical bark scale filter banks to maximize voice energy within frames is introduced. Stable threshold values are obtained at various noise environments (SNR 15 dB, 10 dB, 5 dB, 0 dB). At the test for voice detection in car noisy environment, PHR (Pause Hit Rate) was 100%accurate at every noise environment, and FAR (False Alarm Rate) shows 0% at SNR15 dB and 10 dB, 5.6% at SNR5 dB and 9.5% at SNR0 dB.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1103-1108
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• 2023

In this paper, we propose a new algorithm for attenuating the background noises in acoustic signal. This algorithm improves the noise attenuation performance by using the FNN(: Full-connected Neural Network) deep learning algorithm instead of the existing adaptive filter after wavelet transform. After wavelet transforming the input signal for each short-time period, noise is removed from a single input audio signal containing noise by using a 1024-1024-512-neuron FNN deep learning model. This transforms the time-domain voice signal into the time-frequency domain so that the noise characteristics are well expressed, and effectively predicts voice in a noisy environment through supervised learning using the conversion parameter of the pure voice signal for the conversion parameter. In order to verify the performance of the noise reduction system proposed in this study, a simulation program using Tensorflow and Keras libraries was written and a simulation was performed. As a result of the experiment, the proposed deep learning algorithm improved Mean Square Error (MSE) by 30% compared to the case of using the existing adaptive filter and by 20% compared to the case of using the STFT(: Short-Time Fourier Transform) transform effect was obtained.

• The Journal of the Acoustical Society of Korea
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• v.35 no.5
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• pp.331-339
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• 2016

This paper suggests an estimation method of the source signal and the channel impulse response (CIR) using ray-based blind deconvolution (RBD) in the underwater acoustic channel environment where Doppler effect exists by the relative motion between source and receiver. It is difficult to estimate the CIR on Doppler effect by the matched filter with a highly Doppler-sensitive waveform such as the m-sequence signal because Doppler shift can severely degrade the correlation between the received signal corrupted by Doppler effect and the original source signal. In this study, the Doppler-shifted source-signal's phase is estimated using the RBD, and the received signal is compensated by it to obtain the Doppler-corrected CIR. It is verified that using the matched filter with the received signal from the experimental data fails to estimate the CIR while the obtained CIR by the suggested method has the similarity to the propagation path of the ray model. Also, the results show that the reconstructed source signal using the RBD has the better Doppler shift compensation than the Doppler-shifted source signal derived from scattering function.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.1
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• pp.10-17
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• 2008

The purpose of this thesis is to reduce of error for source location through acoustic emission(AE) signal, generated elastic wave from crack growth to leak for facility diagnosis. Especially, in order to overcome noise from original signal, this paper proposed enhancement of source location by using noise reduction based on wavelet transform. To evaluate actual performance in experiments, Pencil Lead Break is used crack signal source on the aluminum plate and drain valve of air compressor is used as substitute pressure vessel to generate leak signal. In signal processing, wavelet shrinkage and soft threshold are used to discriminate signal source and then source location techniques have been effectively used with group velocity using material property and time difference between sensor using cross correlation. Source location for crack and leak test have some difference, but the result show that improved 30% with a average length within 10.46mm in crack test and improved 2% compare with average filter in leak test when we applied wavelet transform.

• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.43-50
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• 2021

In Korea, the frequency of soil disasters has soared recently due to increased torrential rains caused by abnormal weather conditions. In particular, soil generated from mountainous areas is flowing into small rivers along valleys, depositing rivers and adding to flood damage. In order to prevent damage from such soil disasters, it is important to predict sediments and to quantitatively identify bed load. In this work, we conducted an experiment to indirectly measure acoustic sensor-based bed load collision sounds using pipe hydrophones, and compared them with raw data by applying denoising methods to improve the reliability of the measured data. As a result, we derive results in a more clear analysis of bed load estimation by correcting noise when the denoising method is applied to raw data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.11
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• pp.2569-2574
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• 2012

HMS(Hull Mount Sonar) equipment mounted on PCC(Patrol Combat Corvette) is suitably designed for active mode, and the specific character of sensor or system is not appropriate for the frequency range to detect a torpedo. In this article, in order to implement the function of detecting torpedoes with HMS of existing PCC, I will analyze the feature of input signals each PCCs and design a circuit to compensate reversely for the input signal in certain frequency. And also, I will suggest the most adequate torpedo defense system suitable for the special operating environment and the characteristic of naval vessels, implementing functions such as AGC of input signal and fixing the frequency range of different input signals per different warships.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.5
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• pp.394-400
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• 2010

In this paper, We proposed electronic ballast that applys Buck Converter operation principle to Full-Bridge inverter. The proposed ballast consists of an EMI Filter, a full-bridge rectifier, a passive power factor correction (PFC) circuit and a full-bridge inverter. The passive PFC is used and a Full-Bridge inverter operation by two frequency. High Side and Low Side switch was driven by high frequency and low frequency and realized buck Converter's operation. The lamp is driven by Low Frequency square wave to avoid Acoustic Resonance. Also, bulk of inductor is reduced by high frequency switching. Performance of the proposed ballast was validated through computer simulation using Pspice, experimentation and by applying it to an electronic ballast for a prototype 700W MHL.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.10
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• pp.116-122
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• 2016

This paper proposes a practical object shape reconstruction method using an underwater imaging sonar. In order to reconstruct the object shape, three methods are utilized. Firstly, the vertical field of view of imaging sonar is modified to narrow angle to reduce an uncertainty of estimated 3D position. The wide vertical field of view makes the incorrect estimation result about the 3D position of the underwater object. Secondly, simple noise filtering and range detection methods are designed to extract a distance from the sonar image. Lastly, a low pass filter is adopted to estimate a probability of voxel occupancy. To demonstrate the proposed methods, object shape reconstruction for three sample objects was performed in a basin and results are explained.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.159-166
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• 2005

This thesis deals with a method to deliver more realistic sound by cancelling the cross-talk which is inherent to the 5.1 channel speaker system. First, the cross-talk cancellation method that eliminates cross-talks on the path from left speaker to right ear and from right speaker to left ear is explained. Then the application and replaying method using the cross-talk cancellation explained here is introduced. The acoustical model for cross-talk cancellation is the free field model This model minimizes distortion of sound. Many experts also make studies on this model. I used the bark scale sound quality compensation based on psycho-acoustic. For the surround channels, band-limited sound quality compensation is performed in the frequency domain.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.242-253
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• 2022

When the source waveform is unknown, the Green's function can be estimated by Ray-based Blind Deconvolution (RBD) based on the simple array signal processing. In previous papers, RBD was successfully demonstrated using simulation and experiments in shallow water environment. In this paper, we investigate the applicability of RBD for a long-range communication (e.g., 30 km, 60 km, and 90 km) in a deep water environment (1,000 m ~), using experimental data conducted in the east of Pohang, South Korea, in October 2018. Data results are presented to demonstrate Green's function estimation of a communication signal (2.2 kHz ~ 2.9 kHz) using a 16-element, 42-m long vertical array. The results show that the Green's function estimated from RBD is comparable to that of matched filter result. Additional communication performance at a maximum range of 90 km will be also presented.