• Journal of Advanced Navigation Technology
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• v.26 no.3
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• pp.166-171
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• 2022

In this paper, we propose an algorithm to improve DoA(direction of arrival) estimation performance of the subspace-based method by generating high robustness correlation matrix of the signals incident on the uniformly linear array antenna. The existing subspace-based DoA estimation method estimates the DoA by obtaining a correlation matrix and dividing it into a signal subspace and a noise subspace. However, the component of the correlation matrix obtained from the low SNR and small number of snapshots inaccurately estimates the signal subspace due to the noise component of the antenna, thereby degrading the DoA estimation performance. Therefore a robust correlation matrix is generated by arranging virtual signal vectors obtained from the existing correlation matrix in a sliding manner. As a result of simulation using MUSIC and ESPRIT, which are representative subspace-based methods,, the computational complexity increased by less than 2.5% compared to the existing correlation matrix, but both MUSIC and ESPRIT based on RMSE 1° showed superior DoA estimation performance with an SNR of 3dB or more.

• The Journal of the Acoustical Society of Korea
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• v.25 no.6
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• pp.269-276
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• 2006

In this paper, we propose an emotion recognition system that can discriminate human emotional state into neutral or anger from the speech captured by a cellular-phone in real time. In general. the speech through the mobile network contains environment noise and network noise, thus it can causes serious System performance degradation due to the distortion in emotional features of the query speech. In order to minimize the effect of these noise and so improve the system performance, we adopt a simple MA (Moving Average) filter which has relatively simple structure and low computational complexity, to alleviate the distortion in the emotional feature vector. Then a SFS (Sequential Forward Selection) feature optimization method is implemented to further improve and stabilize the system performance. Two pattern recognition method such as k-NN and SVM is compared for emotional state classification. The experimental results indicate that the proposed method provides very stable and successful emotional classification performance such as 86.5%. so that it will be very useful in application areas such as customer call-center.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.198-204
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• 2024

LDPC, known for its excellent error correction capability, has been adopted as the channel coding technique in the IRIG 106 standard, which is standard for data transmission methods in the aerospace field. Iterative codes such as LDPC require large block sizes and number of iterations in order to improve performance. However, large number of iterations induce computational complexity and power consumption. To solve these problems, this paper presents a parity check-based early stop algorithm that reduces the average number of iterations while maintaining the same performance. BER performance and iteration reduction amounts are compared between early stop algorithm and conventional method that has fixed number of iterations for various coding rate and information bit size defined in the IRIG 106 standard. Through simulation results, we confirmed required iteration numbers are reduced about 50% above without performance loss.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.2
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• pp.129-137
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• 2001

Matching pursuit algorithm was successfully demonstrated useful in low bit-rate video coding, However, one of the practical concerns related to applying the matching pursuit algorithm to application is its massive computation required for finding bases whose weighted sum best approximates the given input image. The main contribution of this paper is that we provide a new method that can drastically reduce the computational load without any degradation of image quality. Its main idea is based on reducing the number of inner product calculation required for finding best bases because the complexity of matching pursuit algorithm is due to the exhaustive local inner product calculation. As the first step, we compute a matrix which is the 1-D inner product of the given motion-compensated error input image with the 1-D vertical Gabor functions using the separable property of Gabor bases. In the second step, we calculate length of each vector in the matrix that corresponds to 1-D horizontal Gabor function, and compare the length with the current maximum absolute inner product value so far. According to the result of this comparison, one can decide whether or not to calculate the inner product. Since most of them do not need to calculate the inner product value, one can significantly reduce the computational load. Experimental results show that proposed method reduces about 70% of inner product calculation compared to the Neff's fast algorithm without any degradation of image quality.

• Journal of Communications and Networks
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• v.12 no.4
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• pp.289-307
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• 2010

The problem of model selection arises in a number of contexts, such as subset selection in linear regression, estimation of structures in graphical models, and signal denoising. This paper studies non-asymptotic model selection for the general case of arbitrary (random or deterministic) design matrices and arbitrary nonzero entries of the signal. In this regard, it generalizes the notion of incoherence in the existing literature on model selection and introduces two fundamental measures of coherence-termed as the worst-case coherence and the average coherence-among the columns of a design matrix. It utilizes these two measures of coherence to provide an in-depth analysis of a simple, model-order agnostic one-step thresholding (OST) algorithm for model selection and proves that OST is feasible for exact as well as partial model selection as long as the design matrix obeys an easily verifiable property, which is termed as the coherence property. One of the key insights offered by the ensuing analysis in this regard is that OST can successfully carry out model selection even when methods based on convex optimization such as the lasso fail due to the rank deficiency of the submatrices of the design matrix. In addition, the paper establishes that if the design matrix has reasonably small worst-case and average coherence then OST performs near-optimally when either (i) the energy of any nonzero entry of the signal is close to the average signal energy per nonzero entry or (ii) the signal-to-noise ratio in the measurement system is not too high. Finally, two other key contributions of the paper are that (i) it provides bounds on the average coherence of Gaussian matrices and Gabor frames, and (ii) it extends the results on model selection using OST to low-complexity, model-order agnostic recovery of sparse signals with arbitrary nonzero entries. In particular, this part of the analysis in the paper implies that an Alltop Gabor frame together with OST can successfully carry out model selection and recovery of sparse signals irrespective of the phases of the nonzero entries even if the number of nonzero entries scales almost linearly with the number of rows of the Alltop Gabor frame.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.11 s.353
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• pp.26-36
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• 2006

In this paper, we propose a cost-effective color filter may (CFA) demosaicing method for digital still cameras in which a single CCD or CMOS image sensor is used. Since a CFA is adopted, we must interpolate missing color values in the red, green and blue channels at each pixel location. While most state-of-the-art algorithms invest a great deal of computational effort in the enhancement of the reconstructed image to overcome the color artifacts, we focus on eliminating the color artifacts with low computational complexity. Using spatial correlation of the adjacent pixels, the edge-directional information of the neighbor pixels is used for determining the edge direction of the current pixel. We apply our method to the state-of-the-art algorithms which use edge-directed methods to interpolate the missing color channels. The experiment results show that the proposed method enhances the demosaiced image qualify from $0.09{\sim}0.47dB$ in PSNR depending on the basis algorithm by removing most of the color artifacts. The proposed method was implemented and verified successfully using verilog HDL and FPGA. It was synthesized to gate-level circuits using 0.25um CMOS standard cell library. The total logic gate count is 12K, and five line memories are used.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.703-712
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• 2019

Single image Super-Resolution (SISR) aims to generate a visually pleasing high-resolution image from its degraded low-resolution measurement. In recent years, deep learning - based super - resolution methods have been actively researched and have shown more reliable and high performance. A typical method is WaveletSRNet, which restores high-resolution images through wavelet coefficient learning based on feature maps of images. However, there are two disadvantages in WaveletSRNet. One is a big processing time due to the complexity of the algorithm. The other is not to utilize feature maps efficiently when extracting input image's features. To improve this problems, we propose an efficient single image super resolution method, named RDB-WaveletSRNet. The proposed method uses the residual dense block to effectively extract low-resolution feature maps to improve single image super-resolution performance. We also adjust appropriated growth rates to solve complex computational problems. In addition, wavelet packet decomposition is used to obtain the wavelet coefficients according to the possibility of large scale ratio. In the experimental result on various images, we have proven that the proposed method has faster processing time and better image quality than the conventional methods. Experimental results have shown that the proposed method has better image quality by increasing 0.1813dB of PSNR and 1.17 times faster than the conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.5
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• pp.1325-1341
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• 1998

A conventional CBR channel is now capable of delivering several digitally compressed video programs due to recent advances in video compression, such as MPEG-2, and digital transmission technology. This paper presents a joint video coding scheme that is to maintain a constant sum of bit rates for all the programs but to allow the variable bit rate for individual program in the transimission environment mentioned above. Thus advantages of VBR video compression can be obtained. This paper contributes in two aspects. First, a rate-distortion estimation method for MPEG-2 video is proposed, which enavle us predict the amount of bits and the distortion generated from an encoded picture at a given quantization step size and vice versa. The most attractive features of the proposed rate-distortion estimation method are its accuracy and a computational complexity low enough to be applied to real-time video coding applications. Second, this paper presents an efficient and accurate joint rate control scheme using the rate-distortion estimation results and verifies its performance with experiments. The experimental results show that our coding scheme gives a significant gain even though a small number of video programs are coded jointly. For example, a stable picture quality is maintained among the video programs as well as within a program, and additional extra programs can be transmitted over the same channel bandwidth if the proposed joint video coding scheme is used.

• Journal of Broadcast Engineering
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• v.3 no.1
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• pp.69-84
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• 1998

In digital broadcasting, services such as digital satellite TV, cable TV and digital terrestrial TV, several video programs are compressed by MPEG-2, and then simultaneously transmitted over a conventional CBR (Constant Bit Rate) broadcasting channel. In this paper, we propose a joint quality control scheme to be able to accurately control the relative picture quality among the video programs, which is achieved by simdt;,nL'Ously controlling the video encoders to generate the VBR (Variable Bit Rate) compressed video streams. Our quality control scheme can prevent the video buffer overflow and underflow by total target bit allocation process, and also exactly control the relative picture quality in terms of PSNR (Peak Signal to Noise Ratio) between some programs requiring higher picture quality and others by rate-distortion modification. Furthermore we present a rate-distortion estimation method for MPEG-2 video, which is base of our joint quality control, and verify its performance by experiments. The most attractive features of this estimation method are as follows: 1) computational complexity is low because main operation for the estimation is to calculate the histogram of OCT coefficients into quantizer; 2) estimation results are very accurate enough to be applied to the practical MPEG-2 video coding applications. Simulation results show that the proposed joint quality control scheme accurately controls the relative picture quality among the video progran1s transmitted over a single channel as well as provides more consistent and higher picture quality than independent coding scheme that encodes each program independently.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6B
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• pp.1082-1091
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• 2000

In this paper, the efficient equalization method for OFDM(Orthogonal Frequency Division Multiflexing) System using the QAM(Quadrature Amplitude Modulation) in multipath fading channel is proposed in order to faster and more efficiently equalize the received signals that are sent over real channel. In generally, the one-tap linear equalizers have been used in the frequency-domain as the existing equalization method for OFDM system. In this technique, if characteristics of the channel are changed fast, the one-tap linear equalizers cannot compensate for the distortion due to time variant multipath channels. Therefore, in this paper, we use one-tap non-linear equalizers instead of using one-tap linear equalizers in the frequency-domain, and also use the linear equalizer in the time-domain to compensate the rapid performance reduction at the low SNR(Signal-to-Noise Ratio) that is the disadvantage of the non-linear equalizer. In the frequency-domain, when QAM signals, consisting of in-phase components and quadrature (out-phase) components, are sent over the complex channel, the only in-phase and quadrature components of signals distorted by the multipath fading are changed the same as signals distorted by the noise. So the cross components are canceled in the frequency-domain equalizer. The time-domain equalizer and the adaptive algorithm that has lower-error probability and fast convergence speed are applied to compensate for the error that is caused by canceling the cross components in the frequency-domain equalizer. In the time-domain, To compensate for the performance of frequency-domain equalizer the time-domain equalizes the distorted signals at a frame by using the Gold-code as a training sequence in the receiver after the Gold-codes are inserted into the guard signal in the transmitter. By using the proposed equalization method, we can achieve faster and more efficient equalization method that has the reduced computational complexity and improved performance.