• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.351-354
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• 2007

In recent years, digital processing techniques have been applied diversity of fields. Typical signal processing techniques are speech processing and image processing. And filters for the signal processing can be divided in FIR (finite impulse response) filter and IIR (infinite impulse response) filter. Compared with IIR filter, the FIR Filter has a defect of high-degree, but has a merit of stability and uses simply. Futhermore, FIR filter also has linear phase response characteristics, it is using in fields regarding wave information importantly. To FIR Filter design, the main issue is to remove the Gibbs phenomenon. Therefore, in this paper I was proposed a method using FIR digital filter applied a modified window function and the method was compared with conventional methods.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1455-1464
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• 2006

In this paper, we propose an adaptive image enhancement algorithm. The proposed algorithm is classified with the MIE technique for intensity enhancement of input image and MSE techniques for saturation enhancement. The MIE technique is proposed to control the gamut mapping problem and a sudden change in image-brightness while Luminance signal is processing, The MSE techniques are proposed to control de-saturation or over-saturation while chrominance signal is processing. The proposed algorithm is focused on processing preference color for human vision in order to generate better image quality than the algorithms focused on processing uniformly to whole images, This algorithm can be applied to a monitor, TV and other display devices for high quality image.

• The Journal of the Acoustical Society of Korea
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• v.13 no.1
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• pp.99-107
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• 1994

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.585-590
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• 2004

Many machine failures are not detected well in advance due to the masking of background noise and attenuation of the source signal through the transmission mediums. Advanced signal processing techniques using adaptive filters and higher order statistics have been attempted to extract the source signal from the measured data at the machine surface. In this paper, blind deconvolution using the eigenvector algorithm (EVA) technique is used to recover a damaged bearing signal using only the measured signal at the machine surface. A damaged bearing signal corrupted by noise with varying signal-to-noise (s/n) was used to determine the effectiveness of the technique in detecting an incipient signal and the optimum choice of filter length. The results show that the technique is effective in detecting the source signal with an s/n ratio as low as 0.21, but requires a relatively large filter length.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2636-2640
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• 2003

KARI had developed an Local Area Augmentation System for aircraft precision landing as following ICAO SARPs(Standards and Recommended Practices) draft and FAA's recommended algorithm( carrier smoothing techniques). JPO in charge of managing GPS has introduced the signal structure of GPS modernization program. This paper estimates the accuracy performance of KARI-LAAS with modernized GPS signal but the same processing algorithm.

• The Journal of the Acoustical Society of Korea
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• v.15 no.3E
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• pp.45-59
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• 1996

Generalized iterative methods for reducing noise in contaminated chaotic signals are proposed. These methods minimize a cost function composed of two parts : one containing information that represents how close enhanced signals are to the observed signal and another composed of constraints that fit the dynamics of the system. The convergence conditions and the error systems of the proposed are investigated. As one aspect of noise reduction, the suppression or cancellation of a chaotic interference signal is discussed.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.287-293
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• 2015

This study proposed signal processing techniques and neural network with weighted fuzzy membership functions(NEWFM) to detect epileptic seizure from EEG signals. This study used wavelet transform(WT), sequential increment method, and phase space reconstruction(PSR) as signal processing techniques. In the first step of signal processing techniques, wavelet coefficients were extracted from EEG signals using the WT. In the second step, sequential increment method was used to extract peaks from the wavelet coefficients. In the third step, 3D diagram was produced from the extracted peaks using the PSR. The Euclidean distances and statistical methods were used to extract 16 features used as inputs for NEWFM. The proposed methodology shows that accuracy, specificity, and sensitivity are 97.5%, 100%, 95% with 16 features, respectively.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.E2
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• pp.66-73
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• 2007

The introduction of tracer gas techniques to ventilation studies in indoor environments provides valuable information that used to be unattainable from conventional testing environments. Data acquisition systems (DASs) containing analogue-to-digital (A/D) converters are usually used to function the key role that records signals to storage in digital format. In the testing process, there exist a number of components in the measuring equipment which may produce system-based inference to the monitored results. These unwanted fluctuations may cause significant error in data analysis, especially when non-linear algorithms are involved. In this study, a pre-processor is developed and applied to separate the unwanted fluctuations (noise or interference) in raw measurements and to reduce the uncertainty in the measurement. Moving average, notch filter, FIR (Finite Impulse Response) filters, and IIR (Infinite Impulse Response) filters are designed and applied to collect the desired information from the raw measurements. Tracer gas concentrations are monitored during leakage and ventilation tests in the model test room. The signal analysis functions are introduced to carry out the digital signal processing (DSP) work. Overall the FIR filters process the $CO_2$ measurement properly for ventilation rate and mean age of air calculations. It is found that, the Kaiser filter was the most applicable digital filter for pre-processing the tracer gas measurements. Although the IIR filters help to reduce the random noise in the data, they cause considerable changes to the filtered data, which is not desirable.

• 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 Sensor Science and Technology
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• v.21 no.1
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• pp.39-45
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• 2012

Recently the convergence of healthcare technology is used for daily life healthcare monitoring. Cardiac arrhythmia is presented by the state of the heart irregularity. Abnormal heart's electrical signal pathway or heart's tissue disorder could be the cause of cardiac arrhythmia. Fatal arrhythmia could put patient's life at risk. Therefore arrhythmia detection is very important. Previous studies on the detection of arrhythmia in various ECG analysis and classification methods had been carried out. In this paper, an ECG signal processing techniques to detect abnormal ECG based on DTW minimum accumulation distance through the template matching for normalized data and variable threshold method for ECG R-peak detection. Signal processing techniques able to determine the occurrence of normal ECG and abnormal ECG. Abnormal ECG detection algorithm using DTW minimum accumulation distance method is performed using MITBIH database for performance evaluation. Experiment result shows the average percentage accuracy of using the propose method for Rpeak detection is 99.63 % and abnormal detection is 99.60 %.