• Proceedings of the IEEK Conference
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• 2000.11a
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• pp.145-148
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• 2000

This paper presents the performance of a GHICW(Group-wise Hybrid Interference Cancellation scheme based on Wiener filtering) receiver for the multi-rate DS-CDMA system. Our scheme has a small processing delay and a simple hardware complexity compared to ordinary interference cancellation schemes by grouping users with the same date rate. The performance improvement of the low rate user is obtained by using a Wiener filter which precisely estimates the high rate users' bit.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.7
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• pp.1290-1294
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• 2008

We present a novel deblurring algorithm for bi-level images blurred by some parameterizable point spread function. The proposed method iteratively searches unknown parameters in the point spread function and noise-to-signal ratio by minimizing an objective function that is based on the binariness and the difference between two intensity values of restoring image. In simulations and experiments, the proposed method showed improved performance compared with the Wiener filtering based method in terms of bit error rate after segmentation.

• The Journal of the Acoustical Society of Korea
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• v.25 no.2E
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• pp.36-42
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• 2006

In this paper, a novel post processing using Wiener filtering technique is proposed to p rm further interference reduction in FDICA. Using the proposed method, the target signal components are remained with little attenuation while the interference components are drastically suppressed. The results of experiments show that the proposed method achieves a reduction of the residual crosstalk. Compared to the NLMS method, the proposed method has slightly better separation performance in SIR, and even requires much less computational complexity.

• The Journal of the Acoustical Society of Korea
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• v.40 no.3
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• pp.213-218
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• 2021

It is known that total least-squares method shows better estimation performance than least-squares method when noise is present at the input and output at the same time. When total least squares method is applied to data with time series characteristics, Recursive Total Least Squares (RTS) algorithm has been proposed to improve the real-time performance. However, RTLS has numerical instability in calculating the inverse matrix. In this paper, we propose an algorithm for reducing numerical instability as well as having similar convergence to RTLS. For this algorithm, we propose a new RTLS using Iterative Wiener Filter (IWF). Through the simulation, it is shown that the convergence of the proposed algorithm is similar to that of the RTLS, and the numerical robustness is superior to the RTLS.

• The Journal of the Acoustical Society of Korea
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• v.8 no.4
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• pp.53-59
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• 1989

A new proposed method can separate heart sounds and lung sounds by the realization of adaptive noise canceler using adaptive lattice Wiener filter in contrast to adaptive transversal LMS filter and high pass filter as before. Lung sounds and ECG signal are detected for this purpose, and especially the second heart sounds are reduced by finding T wave location with a T wave seeking algorithm. As a result, for heart sounds reduction It was found that adaptive transversal LMS filter required 100-200's orders, 75-100's orders In adaptive transversal MLMS filter, and only 10-20's orders in adaptive lattice Wiener filter. Adaptive filtering technique has shown greater accuracy than high pass filtering without loss of low frequency component.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.1867-1872
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• 2016

In the area of digital signal processing, it is necessary to improve the quality of the speech signal after removing the background noise which exists in a various real environments. The important thing to consider when removing the background noise acoustically is that to solve the problem, depending on the information of the human auditory mechanism is mainly the amplitude spectrum of the speech signal. This paper introduces the characteristics of a frequency-weighted spectrum shaping filter for the extraction of the amplitude spectrum of the speech signal with the primary purpose. Therefore, this paper proposes an algorithm using the methods of a Wiener filter and the frequency-weighted spectrum shaping filter according to the acoustic model, after extracted the amplitude spectral information in the noisy speech signal. The spectral distortion (SD) output of the proposed algorithm is experimentally improved more than 5.28 dB compared to a conventional method.

• ETRI Journal
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• v.38 no.2
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• pp.366-375
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• 2016

This paper describes an algorithm to suppress composite noise in a two-microphone speech enhancement system for robust hands-free speech communication. The proposed algorithm has four stages. The first stage estimates the power spectral density of the residual stationary noise, which is based on the detection of nonstationary signal-dominant time-frequency bins (TFBs) at the generalized sidelobe canceller output. Second, speech-dominant TFBs are identified among the previously detected nonstationary signal-dominant TFBs, and power spectral densities of speech and residual nonstationary noise are estimated. In the final stage, the bin-wise output signal-to-noise ratio is obtained with these power estimates and a Wiener post-filter is constructed to attenuate the residual noise. Compared to the conventional beamforming and post-filter algorithms, the proposed speech enhancement algorithm shows significant performance improvement in terms of perceptual evaluation of speech quality.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.415-420
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• 2009

For the emergency detecting in general CCTV environment of our daily life, the monitoring by only images through CCTV information occurs some problems especially in cost as well as man power. Therefore, in this paper, for detecting emergency state dynamically through CCTV as well as resolving some problems, we propose our advanced speech recognition system. For the purpose of it, we adopt HMM(Hidden Markov Model) in our system to do a feature extraction. Also, we adopt Wiener filter technique for noise elimination in many information coming from on CCTV environment. In this paper, our system send only the emergency speech information to a manager to deal with emergency state effectively.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.35-45
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• 2016

To resolve the problems of Poisson/impulse noise, blurriness, and sharpness in degraded X-ray images, a novel and efficient enhancement algorithm based on X-ray image fusion using a discrete wavelet transform is proposed in this paper. The proposed algorithm consists of two basics. First, it applies the techniques of boundary division to detect Poisson and impulse noise corrupted pixels and then uses the Wiener filter approach to restore those corrupted pixels. Second, it applies the sharpening technique to the same degraded X-ray image. Thus, it has two source X-ray images, which individually preserve the enhancement effects. The details and approximations of these sources X-ray images are fused via different fusion rules in the wavelet domain. The results of the experiment show that the proposed algorithm successfully combines the merits of the Wiener filter and sharpening and achieves a significant proficiency in the enhancement of degraded X-ray images exhibiting Poisson noise, blurriness, and edge details.

• Journal of Astronomy and Space Sciences
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• v.30 no.4
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• pp.321-326
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• 2013

The modulation transfer function (MTF) is a widely used indicator in assessments of remote-sensing image quality. This MTF method is also used to restore information to a standard value to compensate for image degradation caused by atmospheric or satellite jitter effects. In this study, we evaluated MTF values as an image quality indicator for the Geostationary Ocean Color Imager (GOCI). GOCI was launched in 2010 to monitor the ocean and coastal areas of the Korean peninsula. We evaluated in-orbit MTF value based on the GOCI image having a 500-m spatial resolution in the first time. The pulse method was selected to estimate a point spread function (PSF) with an optimal natural target such as a Seamangeum Seawall. Finally, image restoration was performed with a Wiener filter (WF) to calculate the PSF value required for the optimal regularization parameter. After application of the WF to the target image, MTF value is improved 35.06%, and the compensated image shows more sharpness comparing with the original image.