• 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 Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.75-80
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• 2021

This paper relates with the Hybrid-DSE-MMA (Hybrid-Dithered Signed Error-MMA) that is possible to improving the equalization performance by using the adaptive modulus and adaptive stepsize in DSE-MMA adaptive equalizer. The DSE-MMA possible to improve the robustness performance to external noise of SE-MMA by using the sign after adding the dither signal for get the error signal in order to update the tap coefficient. But it has a drawback of performance degradation in convergence speed and residual isi by using the fixed modulus and fixed stepsize. In this paper, it was confirmed that this equalization performance degradation was improved by applying the adaptive modulus and stepsize in DSE-MMA propotional to the output power of equalizer by computer simulation. In order to compare the improved equalization performance to currently DSE-MMA, the recovered signal constellation that is the output of the equalizer, residual isi, Maximum Distortion, MSE and the SER were used as a performance index. As a result of computer simulation, the Hybrid-DSE-MMA improve the equalization performance in every index, but gives slower convergence speed compared to DSE-MMA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.45-50
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• 2022

This paper compares the equalization performance of the DSE-MMA (Dithered Signed Error-MMA) and DQE-MMA (Dithered Quantized Error-MMA) adaptive equalization algorithm based on the dither signal in order to reduce the intersymbol interference occurs at communication channel. These algorithm was emerged in ordr to reduction of arithmetic operation than current MMA, it makes the independent and identical distribute the quantized error component by performing the 1 or N bit quautizer after adding the dither singal in obtaining the error signal for adapting process. It is possible to improve the robustness performance of adaptive algorithm, but degrade the MSE performance in steady state by dither signal. The paper directly compare the DSE-MMA and DQE-MMA adaptive equalization performance of the same concept of dithering in the same communication channel and signal to noise ratio by computer simulation. As a result of simulation, the DQE-MMA has more better in the every performance index, equalizer output constellation, residual isi, MSE and SER performance, but not in convergence speed.

• Structural Engineering and Mechanics
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• v.90 no.1
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• pp.19-26
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• 2024

In recent years, an increasing number of experimental studies have shown that the practical application of mature active control systems requires consideration of robustness criteria in the design process, including the reduction of tracking errors, operational resistance to external disturbances, and measurement noise, as well as robustness and stability. Good uncertainty prediction is thus proposed to solve problems caused by poor parameter selection and to remove the effects of dynamic coupling between degrees of freedom (DOF) in nonlinear systems. To overcome the stability problem, this study develops an advanced adaptive predictive fuzzy controller, which not only solves the programming problem of determining system stability but also uses the law of linear matrix inequality (LMI) to modify the fuzzy problem. The following parameters are used to manipulate the fuzzy controller of the robotic system to improve its control performance. The simulations for system uncertainty in the controller design emphasized the use of acceleration feedback for practical reasons. The simulation results also show that the proposed H∞ controller has excellent performance and reliability, and the effectiveness of the LMI-based method is also recognized. Therefore, this dynamic control method is suitable for seismic protection of civil buildings. The objectives of this document are access to adequate, safe, and affordable housing and basic services, promotion of inclusive and sustainable urbanization, implementation of sustainable disaster-resilient construction, sustainable planning, and sustainable management of human settlements. Simulation results of linear and non-linear structures demonstrate the ability of this method to identify structures and their changes due to damage. Therefore, with the continuous development of artificial intelligence and fuzzy theory, it seems that this goal will be achieved in the near future.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.3
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• pp.39-52
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• 1999

In this paper we propose a new watermarking technique for copyright protection of images. The proposed technique is based on a spatial masking method with a spatial scale parameter. In general it becomes more robust against various attacks but with some degradations on the image quality as the amplitude of the watermark increases. On the other hand it becomes perceptually more invisible but more vulnerable to various attacks as the amplitude of the watermark decreases. Thus it is quite complex to decide the compromise between the robustness of watermark and its visibility. We note that watermarking using the spread spectrum is not robust enought. That is there may be some areas in the image that are tolerable to strong watermark signals. However large smooth areas may not be strong enough. Thus in order to enhance the invisibility of watermarked image for those areas the spatial masking characteristics of the HVS(Human Visual System) should be exploited. That is for texture regions the magnitude of the watermark can be large whereas for those smooth regions the magnitude of the watermark can be small. As a result the proposed watermarking algorithm is intend to satisfy both the robustness of watermark and the quality of the image. The experimental results show that the proposed algorithm is robust to image deformations(such as compression adding noise image scaling clipping and collusion attack).

• Journal of the Korea Society of Computer and Information
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• v.18 no.4
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• pp.35-43
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• 2013

As texture images have become prevalent throughout a variety of industrial applications, copyright protection of these images has become important issues. For this reason, this paper proposes a color-texture image watermarking algorithm utilizing texture properties inherent in the image. The proposed algorithm selects suitable blocks to embed a watermark using the energy and homogeneity properties of the grey level co-occurrence matrices as inputs for the fuzzy c-means clustering algorithm. To embed the watermark, we first perform a discrete wavelet transform (DWT) on the selected blocks and choose one of DWT subbands. Then, we embed the watermark into discrete cosine transformed blocks with a gain factor. In this study, we also explore the effects of the DWT subbands and gain factors with respect to the imperceptibility and robustness against various watermarking attacks. Experimental results show that the proposed algorithm achieves higher peak signal-to-noise ratio values (47.66 dB to 48.04 dB) and lower M-SVD values (8.84 to 15.6) when we embedded a watermark into the HH band with a gain factor of 42, which means the proposed algorithm is good enough in terms of imperceptibility. In addition, the proposed algorithm guarantees robustness against various image processing attacks, such as noise addition, filtering, cropping, and JPEG compression yielding higher normalized correlation values (0.7193 to 1).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.79-84
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• 2018

This paper relates with the performance improvement of SE-MMA (Signed Error-Multiple Modulus Algorithm) adaptive equalization algorithm that is used for the reduction of the intersymbol interference due to the distortion which occurs in the communication channel for the transmission of 16-QAM nonconstant modulus signal.. In the conventional MMA, the fixed modulus value that is second order statistics of transmitting signal were used, and the SE-MMA was introduced in order to the simplification of the algorithm's arithmetic operation. The SE-MMA have a fast convergence speed than MMA, but it has a problem of degradation of equalization performance in the steady state due to the arithmetic simplification. In this paper, we propose the new algorithm AV-SE-MMA (Adaptively Varying-SE-MMA) that uses the adaptive varying modulus in order to obtain the error signal for updating the adaptive equalizer coefficient, and its equalization performance were confirmed by simulation. In this paper, the performance of SE-MMA and proposed algorithm were compared, and the equalizer output signal constellation, residual isi, MSE and SER in order to confirm the robustness of noise were used as performace index. As a result of performance comparison, the AV-SE-MMA has better performance in output signal constellation, residual isi and MD compared to the SE-MMA, but it was confirmed that the AV-SE-MMA has similar in the SER performance that means the robustness to the noise.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.12
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• pp.127-134
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• 2005

Lost packet robustness is an most important quality measure for voice over IP networks(VoIP). Recovery of the lost packet from the received information is crucial to realize this robustness. So, this paper proposes the lost packet recovery method from the received information for real-time communication for CELP coder. The proposed BS-PLC (Both Side Packet Loss Concealment) based WSOLA(Waveform Shift OverLab Add) allow the lost packet to be recovered from both the 'previous' and 'next' good packet as the LP parameter and the excitation signal are respectively recovered. The burst of packet loss is modeled by Gilbert model. The proposed scheme is applied to G.729 most used in VoIP and is evaluated through the SNR(signal to noise) and the MOS(Mean Opinion Score) test. As a simulation result, The proposed scheme provide 0.3 higher in Mean Opinion Score and 2 dB higher in terms of SNR than an error concealment procedure in the decoder of G.729 at $20\%$ average packet loss rate.

• Journal of KIISE:Software and Applications
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• v.32 no.7
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• pp.612-624
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• 2005

In this paper, we propose a surface-based registration using a gaussian weighted distance map for PET-CT brain image fusion. Our method is composed of three main steps: the extraction of feature points, the generation of gaussian weighted distance map, and the measure of similarities based on weight. First, we segment head using the inverse region growing and remove noise segmented with head using region growing-based labeling in PET and CT images, respectively. And then, we extract the feature points of the head using sharpening filter. Second, a gaussian weighted distance map is generated from the feature points in CT images. Thus it leads feature points to robustly converge on the optimal location in a large geometrical displacement. Third, weight-based cross-correlation searches for the optimal location using a gaussian weighted distance map of CT images corresponding to the feature points extracted from PET images. In our experiment, we generate software phantom dataset for evaluating accuracy and robustness of our method, and use clinical dataset for computation time and visual inspection. The accuracy test is performed by evaluating root-mean-square-error using arbitrary transformed software phantom dataset. The robustness test is evaluated whether weight-based cross-correlation achieves maximum at optimal location in software phantom dataset with a large geometrical displacement and noise. Experimental results showed that our method gives more accuracy and robust convergence than the conventional surface-based registration.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.6
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• pp.22-31
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• 2000

In this paper, we propose a method for removing noise components in the feature extraction process for robust speech recognition. This method is based on blind separation using independent component analysis (ICA). Given two noisy speech recordings the algorithm linearly separates speech from the unwanted noise signal. To apply ICA as closely as possible to the feature level for recognition, a new spectral analysis is presented. It modifies the computation of band energies by previously averaging out fast Fourier transform (FFT) points in several divided ranges within one met-scaled band. The simple analysis using sample variances of band energies of speech and noise, and recognition experiments showed its noise robustness. For noisy speech signals recorded in real environments, the proposed method which applies ICA to the new spectral analysis improved the recognition performances to a considerable extent, and was particularly effective for low signal-to-noise ratios (SNRs). This method gives some insights into applying ICA to feature levels and appears useful for robust speech recognition.