• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.4
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• pp.200-205
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• 2017

In this paper, we propose a technique to determine the normal and arc of an alternating current using a mixed filter composed of an average filter and a band-pass filter and a frequency analysis. The proposed method uses the moving average filter of the FIR filter structure for noise removal and the band-pass filter of the IIR filter structure for detecting only specific frequency components after normalizing the measured current signal based on the maximum value. After performing Fast Fourier Transform (FFT) using the band-pass filtered signal, the total energy is calculated using the magnitude component of the frequency, and the arc is detected using the magnitude of the calculated energy. In order to show the validity of the proposed method, we experimented with various data and found that arc and steady state can be easily discriminated by calculating spectral energy. Therefore, it is considered that the proposed method can be applied to arc diagnosis of low voltage electric wire.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06e
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• pp.31-34
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• 1998

배경 잡음에 의해 저하된 음성을 복원하는 기술은 이미 오래 전부터 여러 가지 기법들이 연구되어왔다. 이들 기법 중, Spectral Subtraction 기법은 단일 채널에 의한 Speech Enhancement의 대표적인 방법이다. 그러나, 기존의 단일 채널 Speech Enhancement 기법의 중요한 단점은 Musical Noise라 불리는 잔존 Noise의 발생 및 목적신호가 왜곡된다는 것이다. 이 잔존 Noise에 의해 지금까지 연구 보고된 단일 채널 Speech Enhancement기법들은 거의 대부분 SNR은 향상되었지만 명료도의 향상이 곤란하였다고 보고되어왔다. 그러므로, 본 연구에서는 인간의 청각기구의 지각과정을 충실히 모방한 ROEX(Rounded Exponential) 청각 Filter를 이용하여 잔존 Noise인 Musical Noise를 억제시키는 기법을 제안하고자 한다.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2338-2340
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• 2004

탐지레이다 또는 TWS 레이다의 측정 정밀도는 추적 필터 설계에서 quantization 문제로써 고려해야 한다. 본 논문에서는 측정 정밀도가 추적필터에서 quantization 문제로 변환됨을 보이고 오차면적과 추정성능을 비교한다. 또한 오차면적을 줄이는 방안과 quantization이 존재하면 측정잡음과 관계한 공정잡음의 power spectral density를 선정함을 보인다.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.957-962
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• 1994

Real-time RELP vocoder is implemented on the TMS320C25 DSP chip. The implemented system is IBM-PC add-on board and composed of analog in/out unit, DSP unit, memoy unit, IBM-PC interface unit and its supporting assembly software. Speech analyzer and synthesizer is implimented by DSP assembly software. Speech parameters such as LPC coefficients, base-band residuals, and signal gains is extracted by autocorrelation method and inverse filter and synthesized by spectral folding method and direct form synthesis filter in this board. And then, real-time RELP vocoder with 9.6Kbps is simulated by down-loading method in the DSP program RAM.

• Journal of the Korean Geographical Society
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• v.51 no.4
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• pp.509-523
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• 2016

The soil prediction can provide quantitative soil information for sustainable mountainous ecosystem management. Visible near infrared spectroscopy, one of soil prediction methods, has been applied to predict several soil properties with effective costs, rapid and nondesctructive analysis, and satisfactory accuracy. Spectral preprocessing is a essential procedure to correct noisy spectra for visible near infrared spectroscopy. However, there are no attempts to evaluate various spectral preprocessing methods. We tested 5 different pretreatments, namely continuum removal, Savitzky-Golay filter, discrete wavelet transform, 1st derivative, and 2nd derivative to predict soil carbon(C) and nitrogen(N). Partial least squares regression was used for the prediction method. The total of 153 soil samples was split into 122 samples for calibration and 31 samples for validation. In the all range, absorption was increased with increasing C contents. Specifically, the visible region (650nm and 700nm) showed high values of the correlation coefficient with soil C and N contents. For spectral preprocessing methods, continuum removal had the highest prediction accuracy(Root Mean Square Error) for C(9.53mg/g) and N(0.79mg/g). Therefore, continuum removal was selected as the best preprocessing method. Additionally, there were no distinct differences between Savitzky-Golay filter and discrete wavelet transform for visual assessment and the methods showed similar validation results. According to the results, we also recommended Savitzky-Golay filter that is a simple pre-treatment with continuum removal.

• Journal of Korea Multimedia Society
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• v.4 no.1
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• pp.56-66
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• 2001

The spectral subtraction algorithm using a criterion based on the human perception has been recently developed. The speech processed with Virag's algorithm sounds more pleasant to a human listener than those obtained by the classical methods. However, Virag's algorithm requires a robust voice activity detector (VAD). In the ESS (extended spectral subtraction) algorithm without VAD, the residual noise becomes more noticeable as the SNR decrease. In this paper we propose a new speech enhancement method, the combination of Wiener filter and spectral subtraction based on noise masking characteristics in the human auditory system. There is no need of VAD because the noise can be successively updated even during speech activity using Wiener filter. The adjustment of the subtraction parameter based on the masking threshold makes the residual noise inaudible. The proposed method has been compared with conventional spectral subtraction algorithms. Objective and subjective evaluation of the proposed system is performed with several noise types having different time-frequency distributions. The application of objective measures, the study of the speech spectrograms, as well as subjective listening tests, confirm that the enhanced speech with proposed algorithm is more pleasant to a human listener.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.5
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• pp.31-36
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• 2011

In this paper, Mel-Frequency Cepstral Coefficient (MFCC), Decorrelated Filter Bank (DFB), Octave-based Spectral Contrast (OSC), Zero-Crossing Rate (ZCR), and Spectral Contract/Roll-Off are combined as a set of multiple feature-vectors for the music genre classification system based on the Support Vector Machine (SVM) classifier. In the conventional system, feature vectors for the entire genre classes are normalized for the SVM model training and classification. However, in this paper, selected feature vectors that are compared based on the One-Against-One (OAO) SVM classifier are only used for normalization. Using OSC as a single feature-vector and the multiple feature-vectors, we obtain the genre classification rates of 60.8% and 77.4%, respectively, with the conventional normalization method. Using the proposed normalization method, we obtain the increased classification rates by 8.2% and 3.3% for OSC and the multiple feature-vectors, respectively.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.177-186
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• 2023

Hyperspectral imaging technology is one of the most efficient and fast-growing technologies in recent years. Hyperspectral image (HSI) comprises contiguous spectral bands for every pixel that is used to detect the object with significant accuracy and details. HSI contains high dimensionality of spectral information which is not easy to classify every pixel. To confront the problem, we propose a novel RGB channel Assimilation for classification methods. The color features are extracted by using chromaticity computation. Additionally, this work discusses the classification of hyperspectral image based on Domain Transform Interpolated Convolution Filter (DTICF) and 3D-CNN with Bi-directional-Long Short Term Memory (Bi-LSTM). There are three steps for the proposed techniques: First, HSI data is converted to RGB images with spatial features. Before using the DTICF, the RGB images of HSI and patch of the input image from raw HSI are integrated. Afterward, the pair features of spectral and spatial are excerpted using DTICF from integrated HSI. Those obtained spatial and spectral features are finally given into the designed 3D-CNN with Bi-LSTM framework. In the second step, the excerpted color features are classified by 2D-CNN. The probabilistic classification map of 3D-CNN-Bi-LSTM, and 2D-CNN are fused. In the last step, additionally, Markov Random Field (MRF) is utilized for improving the fused probabilistic classification map efficiently. Based on the experimental results, two different hyperspectral images prove that novel RGB channel assimilation of DTICF-3D-CNN-Bi-LSTM approach is more important and provides good classification results compared to other classification approaches.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.5
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• pp.15-24
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• 1997

We propose a tunable add/drop filter in a form of an all-fiber mach-zehnder interferometer iwth one bragg grating at each arm. This device can be tuned by inducing a strain in the bragg grating. We also theoretically analyze the outut characteristics of the tunable add/drop filter. As a result of simulation, we know that the proposed tunable add/drop filter works well. When 2*10$^{-3}$ of strain is induced, the reflected spectrum shifts about 3nm. And its reflected spectral width is about 0.3nm. In this case roughly 5 channels can be tuned, assuming the channel spacing is 0.3nm. When the pathlengths of the both arms are not the same, the transmissivities at the add and output ports and the reflectivity at the tap port varies sinusoidally with the pthlength difference. To maintain the transmissivities above 90% in the wavelength tuning range of 20nm the pathlength difference less than 16.mu.m is required.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.138-144
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• 2015

Digital filters are extensively used in the world of communication. In order to design a digital finite impulse response (FIR) filter that satisfies all the required conditions is challenging. In this paper, design techniques of digital low pass FIR filters using Rectangular window method, Hamming window, Hanning window, and Optimal Parks McClellan method are presented. The stability, number of components required and filter coefficients are demonstrated for different design techniques. It is demonstrated that filter design using hamming window is comparatively better than rectangular and hanning window though the components required for all of the windowing technique are same, hamming shows higher stability. The stability is shown with the help of magnitude and phase spectrum of each window. Simulation is carried out using MATLAB and comparisons are made entirely based on the output of the simulation.