• Journal of Digital Convergence
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• v.11 no.6
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• pp.169-174
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• 2013

Speech recognition, the problem of performance degradation is the difference between the model training and recognition environments. Silence features normalized using the method as a way to reduce the inconsistency of such an environment. Silence features normalized way of existing in the low signal-to-noise ratio. Increase the energy level of the silence interval for voice and non-voice classification accuracy due to the falling. There is a problem in the recognition performance is degraded. This paper proposed a robust speech detection method in noisy environments using a silence feature normalization and voice energy maximize. In the high signal-to-noise ratio for the proposed method was used to maximize the characteristics receive less characterized the effects of noise by the voice energy. Cepstral feature distribution of voice / non-voice characteristics in the low signal-to-noise ratio and improves the recognition performance. Result of the recognition experiment, recognition performance improved compared to the conventional method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.8
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• pp.1713-1718
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• 2004

It has been known that 1/f noise of MOSFET is generated by the superposition of single random telelgraph signals (RTS). In this study, jitters caused by 1/f noise of MOSFET are analysed with RTS supplied to all of the nodes of the CMOS ring oscillator under investigation. Through the analysis of the variations of jitters and jitter ratios with varying values of the amplitude of RTS, it is found that the jitters and the jitter ratios are proportional to the amplitude of RTS. And the analysis of FFT of the outputs of the ring oscillator reveals that the jitters are closely related to the phase noise of the high order harmonics of the ring oscillator outputs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.681-683
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• 2017

In the digital information age, image processing is essential for various digital devices such as smart phones, cameras, and TVs. However, degradation occurs in analyzing, recognizing, and processing image data, and salt & pepper noise occurs. Therefore, in this paper, we applied linear interpolation method, newton interpolation method, lagrange interpolation method, and spline interpolation method to the image damaged by salt & pepper noise in order to find more effective interpolation method in salt & pepper noise environment, The methods were compared using the PSNR (peak signal to noise ratio).

• Korean Journal of Remote Sensing
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• v.19 no.1
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• pp.43-52
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• 2003

EOC (Electro-Optical Camera) of KOMPSAT-1 (Korea Multi-Purpose SATellite) has been producing land imageries of the world since January 2000. After image data are acquired by EOC, they are transmitted from satellite to ground via X-band RF signal. Then, EOC image data are retrieved and pass through radiometric and geometric corrections to generate standard products of EOC images. After radiometric correction on EOC image data, Modulation Transfer Function (MTF) compensation is applicable on EOC images with user's request for better image quality. MTF compensation is concerned with filtering EOC images to minimize the effect of degradations. For Image Receiving and Processing System (IRPE) at KOMPSAT Ground Station (KGS), Wiener filter is used for MTF compensation of EOC images. If the Pointing Spread Function (PSF) of EOC system is known, signal-to-noise (SNR) power spectra ratio is the only variable which determines the shape of Wiener filter In this paper, MTF compensation in IRPE at KGS is briefly addressed, and MTF compensated EOC images are generated using Wiener filters with various SNR power spectra ratios. MTF compensated EOC images are compared with original EOC 1R images to observe correlations between them. As a result, the effect of SNR power spectra ratio on MTF compensated EOC images is shown.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.973-979
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• 2011

In the transmitting process of image signal processing system, there are several different causes of degradation that have been occurring. The main cause of degradation is attributed to the noise. The most representive method of removing noise of image, which is caused by impulse noise environment, is using the SM(standard median filter). At edge, the filter has a special feature which has a tendency to decrease. As a result, we proposed a nonlinear filter that restores the image considering edge quality in the impulse noise environment. And through the simulation, we compared with the many of the conventional algorithms and the value of the PSNR(peak signal to nise ratio) is better than them and preserve the edge very well. So the nonlinear filter that proposed in this paper is excepted to help improve restoring the images that in impulse noise environment.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.2
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• pp.118-126
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• 2004

The modified Wiener filtering method is proposed for effective noise suppression in edge region of images corrupted by additive white gaussian noise. Although the pixels classified as a edge region in the conventional Wiener filter have lots of noise components, the conventional Wiener filter cannot remove noise effectively due to the preserving of edges. To reduce noise well in edge region, we modify filter coefficients of the conventional Wiener filter. The modified filter coefficients increase in noise suppression effect in edge region, while they preserve edges for strong edge region. From simulation (256${\times}$256 size, 256 graylevel images) filtered images by the proposed method show much improved subjective image quality with higher peak signal-to-noise ratio compared to those by the conventional Wiener filtering.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1999-2005
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• 2005

Collaboration in wireless sensor networks must be fault-tolerant due to the harsh environmental conditions in which such networks can be deployed. This paper focuses on finding signal processing algorithms for collaborative target detection based on the generalized approach to signal processing in the presence of noise that are efficient in terms of communication cost, precision, accuracy, and number of faulty sensors tolerable in the wireless sensor network. Two algorithms, namely, value fusion and decision fusion constructed according to the generalized approach to signal processing in the presence of noise, are identified first. When comparing their performance and communication overhead, decision fusion is found to become superior to value fusion as the ratio of faulty sensors to fault free sensors increases. The use of the generalized approach to signal processing in the presence of noise under designing value and decision fusion algorithms in wireless sensor networks allows us to obtain the same performance, but at low values of signal energy, as under the employment of universally adopted signal processing algorithms widely used in practice.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.72-80
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• 1996

In this paper, variable windowing mean filter to remove speckle noise and a measure to detect thin edge in ultrasonic images are proposed. Because ultrasonic images are corrupted by speckle noise showing a granular appearance, good edge detection is difficult. As a result, noise removing filter is needed in preprocessing stage. The speckle noise removing filter is based on mean filter whose window size is changed by the ratio of standard deviation to mean for image signal and noise signal in local area. And the measure expressed the difference of means between tow windows is used for detecting thin edge in filtered image. Results show that variable windowing mean filter removes speckle noise effectively, and proposed measure is useful in detecting thin edge.

• Journal of Sensor Science and Technology
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• v.6 no.6
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• pp.458-465
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• 1997

In this paper, a theory of the geological magnetic filter for the improvements of the signal to noise ratio of the magnetic detection system has been developed. The geological magnetic filter takes two sequences of magnetic fields measured from the reference sensor and the detector sensor and calculate the correlations between them in the frequency domain. Using the filter, we can remove the coherent noises in the time domain and improve the signal to noise ratio of the magnetic detection system. With the recent developments of the DSP hardware technology the geological magnetic filter can be easily implemented using the digital signal processor. We show the ability of the geological magnetic filter under various circumstances through computer simulations. Numerical simulation results show that geological magnetic filter can excellently remove the sensor misalignment effects and the regular short range local noise as well as it delete the coherent noises.

• Current Optics and Photonics
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• v.7 no.6
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• pp.683-691
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• 2023

A typical terahertz time-domain spectroscopy system requires large, expensive, and heavy hardware such as a lock-in amplifier and a function generator. In this study, we replaced the lock-in amplifier and the function generator with a single sound card built into a typical desktop computer to significantly reduce the system size, weight, and cost. The sound card serves two purposes: 1 kHz chopping signal generation and raw data acquisition. A unique software lock-in (Python coding program to eliminate noise from raw data) method was developed and successfully extracted THz time-domain signals with a signal-to-noise ratio of ~40,000 (the intensity ratio between the peak and average noise levels). The built-in sound card with the software lock-in method exhibited sufficiently good performance compared with the hardware-based method.