• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.145-155
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• 2015

Noise reduction has been actively studied in the digital image processing and recently, block-based denoising algorithms are widely used. In particular, a low rank approximation employing WNNM(Weighted Nuclear Norm Minimization) and block-based approaches demonstrated the potential for effective noise reduction. However, the algorithm based on low rank a approximation generates the artifacts in the image restoration step. In this paper, we analyzes the image content using the STFT(Short Time Fourier Transform) and proposes an effective method of minimizing the artifacts generated from the conventional algorithm. To evaluate the performance of the proposed scheme, we use the test images containing a wide range of noise levels and compare the results with the state-of-art algorithms.

• The Journal of the Acoustical Society of Korea
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• v.43 no.5
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• pp.502-510
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• 2024

In this paper, we proposed the weakly-supervised deep learning algorithm for active sonar target recognition based on pseudo labeling using Conventional Recurrent Neural Network (CRNN) model widely used for acoustic signal processing because it can effectively utilize small and unbalanced active sonar data. Active sonar simulation data assuming two different SNRs and clutter environments were used in the training and testing process, and spectrogram obtained by applying Short Time Fourier Transform (STFT) to the simulation data was used as a feature factor for algorithm training. The algorithm proposed in this paper was evaluated based on the target and nontarget F1-score using test data independent of training data. As a result, it was confirmed that the CRNN model showed significant performance not only in typical acoustic signal processing but also active sonar target recognition. Also, pseudo-labeling helps to improve the performance of the active sonar target recognition algorithm used the CRNN model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.628-631
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• 2008

For the remote sensing purpose, radar systems extract the target information, such as the magnitude of reflectivity and the velocity from the spectrum analysis of return echoes through the Doppler filter bank. This conventional spectrum estimation method, FFT(Fast fourier Transform) is widely used in most radar systems. However, the frequency resolution of return echoes can be seriously degraded in fast moving targets because of the short acquisition time. Since the high Doppler frequency resolution is important in the detection and tracking of fast moving targets, it can cause very unsatisfactory results. Therefore, in this paper, the parameter spectrum estimation method called AR(Autoregressive) spectrum estimation, is investigated to overcome these problems.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2010.11a
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• pp.469-473
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• 2010

In this study, combustion tests using liquefying fuels with fast regression rate were performed. The chamber pressure oscillation was analyzed and hazards of combustion instabilities were examined. In case of Liquefying fuel with fast regression rate, the amplitude of chamber pressure oscillation was increased compared to the polymeric fuels. However, the critical combustion instability can hardly occur in liquefying fuel. This is because the rapid change of inner chamber diameter limits the amplification of chamber pressure oscillation. The chamber pressure oscillation due to the large increase of fuel production and the vortex shedding in pre-chamber violently occurs during combustion using single-port axial injector.

• Journal of Sensor Science and Technology
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• v.32 no.4
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• pp.246-251
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• 2023

Internet of Things (IoT) systems process signals from various sensors using signal processing algorithms suitable for the signal characteristics. To analyze complex signals, these systems usually use signal processing algorithms in the frequency domain, such as fast Fourier transform (FFT), filtering, and short-time Fourier transform (STFT). In this study, we propose a multi-mode sensor signal processor (SSP) accelerator with an FFT-based hardware design. The FFT processor in the proposed SSP is designed with a radix-2 single-path delay feedback (R2SDF) pipeline architecture for high-speed operation. Moreover, based on this FFT processor, the proposed SSP can perform filtering and STFT operation. The proposed SSP is implemented on a field-programmable gate array (FPGA). By sharing the FFT processor for each algorithm, the required hardware resources are significantly reduced. The proposed SSP is implemented and verified on Xilinxh's Zynq Ultrascale+ MPSoC ZCU104 with 53,591 look-up tables (LUTs), 71,451 flip-flops (FFs), and 44 digital signal processors (DSPs). The FFT, filtering, and STFT algorithm implementations on the proposed SSP achieve 185x average acceleration.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.3 s.108
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• pp.255-262
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• 2006

Frequency spectrum using the conventional Fourier analysis gives adequate information about the dynamic characteristics of the slider air bearing for the linear and stationary cases. The intermittent contacts for the extremely low flying height, however, generate nonlinear and nonstationary vibration at the instant of contact. Nonlinear dynamic model should be developed to simulate the impulse response of the air bearing during slider-disk contact. Time-frequency analysis is widely used to investigate the nonstationary signal. Several time-frequency analysis methods are employed and compared for the slider vibration signal caused by the impact against an artificially induced scratch on the disk. The representative Wigner-Ville distribution leads to the severe interference problem by cross terms even though it gives good resolution both in time and frequency. The smoothing process improves the interference problem at the expense of resolution. In order to get the results with good resolution and little interference, the reassignment method is proposed. Among others the reassigned Gabor spectrogram shows the best resolution and readability with negligible interference.

• The Journal of the Acoustical Society of Korea
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• v.23 no.1
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• pp.8-16
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• 2004

An inversion method is presented for the determination of the compressional wave speed, compressional wave attenuation, thickness of the sediment layer and density as a function of depth for a horizontally stratified ocean bottom. An experiment for estimating those properties was conducted in the shallow water of South Sea in Korea. In the experiment, a light bulb implosion and the propagating sound were measured using a VLA (vertical line array). As a method for estimating the geoacoustic properties, a coherent broadband matched field processing combined with Genetic Algorithm was employed. When a time-dependent signal is very short, the Fourier transform results are not accurate, since the frequency components are not locatable in time and the windowed Fourier transform is limited by the length of the window. However, it is possible to do this using the wavelet transform a transform that yields a time-frequency representation of a signal. In this study, this transform is used to identify and extract the acoustic components from multipath time series. The inversion is formulated as an optimization problem which maximizes the cost function defined as a normalized correlation between the measured and modeled signals in the wavelet transform coefficient vector. The experiments and procedures for deploying the light bulbs and the coherent broadband inversion method are described, and the estimated geoacoustic profile in the vicinity of the VLA site is presented.

• Composites Research
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• v.13 no.1
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• pp.40-49
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• 2000

The objective of this research is to develop the impact monitoring techniques providing impact identification and damage diagnostics of smart composite laminates susceptible to impacts. This can be implemented simultaneously by using the acoustic waves by the impact loads and the acoustic emission waves from damage. In the previous research, we have discussed the impact location detection process in which impact generated acoustic waves are detected by PZT using the improved neural network paradigm. This paper describes the implementation of time-frequency analysis such as the Short-Time Fourier Transform (STFT) and the Wavelet Transform (WT) on the determination of the occurrence and the estimation of damage.

• Speech Sciences
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• v.7 no.1
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• pp.17-29
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• 2000

The STC(Sinusoidal Transform Coding) is a vocoding technique that uses a sinusoidal speech model to obtain high- quality speech at low data rate. It models and synthesizes the speech signal with fundamental frequency and its harmonic elements in frequency domain. To reduce the data rate, it is necessary to represent the sinusoidal amplitudes and phases with as small number of peaks as possible while maintaining the speech quality. As a basic research to develop a low-rate speech coding algorithm using the sinusoidal model, in this paper, we investigate the speech quality depending on the number of sinusoids. By varying the number of spectral peaks from 5 to 40 speech signals are reconstructed, and then their qualities are evaluated using spectral envelope distortion measure and MOS(Mean Opinion Score). Two approaches are used to obtain the spectral peaks: one is a conventional STFT (Short-Time Fourier Transform), and the other is a multiresolutional analysis method.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2003.10a
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• pp.158-162
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• 2003

The PVDF(polyvinylidene fluoride) film sensor as one of smart sensors has good characteristics to detect the impact damages of composite structures. The capabilities of the PVDF film sensor for evaluating impact behaviors and damages of Gr/Ep laminates subjected to low-velocity impact were examined. From sensor signals, the specific wave-forms implying the damage were detected. The wavelet transform(WT) and Short Time Fourier Transform(STFT) were used to decompose the piezoelectric sensor signals in this study. The impact behaviors of Gr/Ep laminates were simulated and the impact forces were reconstructed using the sensor signals. Finally, the impact damages were predicted by finite element analysis with the reconstructed forces. For experimental verification, a series of low-velocity impact tests from low energy to damage-induced energy were carried-out. The extent of damage in each case was examined by means of ultrasonic C-scan and the measured damage areas were agreed well with the predicted areas by the F.E.A.