• Journal of Communications and Networks
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• v.13 no.2
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• pp.167-174
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• 2011

In this paper, we propose and simulate an efficient interference cancellation scheme with an optimal ordering successive interference cancellation (SIC) algorithm for ultra wideband (UWB)/multiple-input-multiple-output (MIMO) systems in a wireless body area network (WBAN). When there are several wireless communication devices on a human body, multiple access interference (MAI) usually occurs. To mitigate the effect of MAI and achieve additional diversity gain, we utilize SIC with an optimal ordering algorithm. A zero correlation duration (ZCD) code with robust MAI capability is employed as a spread code for UWB systems in a multi-device WBAN environment. The performance of the proposed scheme is evaluated in terms of the bit error rate (BER). Simulation results confirm that the BER performance can be improved significantly if the proposed interference cancellation scheme and the ZCD code are jointly employed.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2949-2952
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• 2000

A new neural networks and learning algorithm are proposed in order to measure nonlinear heights of complexed road environments in realtime without pre-information. This new neural networks is Error Self Recurrent Neural Networks(ESRN), The structure of it is similar to recurrent neural networks: a delayed output as the input and a delayed error between the output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by back-propagation and each weights are updated by RLS(Recursive Least Square). Consequently. this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. We can estimate nonlinear models in realtime by ESRN and learning algorithm and control nonlinear models. To show the performance of this one. we control 7 degree of freedom full car model with several control method. From this simulation. this estimation and controller were proved to be effective to the measurements of nonlinear road environment systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.10
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• pp.934-940
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• 1991

A modified quantizing method is introduced to teach single layer learning algorithm, which is implemented optically. The proposed optical system consists of input masks, holographic diffraction grating. LCD and CCD camera. The 2 dimensional interconnections between input neurons and output neurons are realized using holographic phase grating, which is fabricated for equal intensity distribution of diffraction orders. The two gray levels of LCD act as binary weights for each interconnection. The weights are compensated according to the learning algorithm in which the amount of weights to be compensated is determined by comparing the output patterns with target patterns. The learning process is iterated until the predetermined conditions are satisfied. Optical experiments are performed for two learning rates, 0.5 and 0.9 and the experimental results show that the proposed system is useful for optical neural networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9B
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• pp.1609-1617
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• 2000

In this paper a design of cryptographic coprocessor which implements SEED algorithm is described. To satisfy trade-off between area and speed, the coprocessor has structure in which 1 round operation is divided into three subrounds and then subround is executed for one clock. To improve clock frequency online precomputation scheme for round key is used. To apply the coprocessor to various applications, four operating modes such as ECB, CBC, CFB, and OFB are supported. Also to eliminate performance degradation due to data input and data output time between host computer and coprocesor, background input/output method is used. The cryptographic coprocessor is designed using $0.25{\mu}{\textrm}{m}$ CMOS technology and consists of about 29,300 gates. Its peak performance is about 237 Mbps encryption or decryption rate under 100 Mhz clock frequncy and ECB mode.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3A
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• pp.276-283
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• 2002

This paper proposes a new color constancy algorithm using the maximum luminance surface. This method uses a linear model which represents the characteristics of human visual system. The most important process of linear model is the estimation of the spectral distributions of illumination from an input image. To estimate of the spectral distributions of illumination from an input image, we first estimate spectral distribution functions of reflected light on the brightest surface. Then, we estimate surface reflectance functions corresponding to the maximum luminance surface using a principal component analysis of the given munsell chips. We finally estimate the spectral distributions of illumination in an image. Using an estimated illumination, we recover an image by scaling it regularly for the lightness calibration. From the experimental results, the proposed method was effective in recovering the color images compared with others.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1140-1155
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• 2021

Up to now, many state-of-arts have been proposed for two-way relaying system with linear modulations. The performances of antenna selection (AS) at both transmit and relay nodes need to be investigated in some two-way relaying multiple-input multiple-output (TWRM) systems. In this paper, the goal is focused on the study of nonlinear modulations, i.e., continuous phase modulation (CPM) in TWRM systems. Firstly, the joint phase trellis are simplified by reversed Rimoldi processing so as to reduce the systems' complexity. Then the performances of joint transmit and receive antenna selection (JTRAS) with CPM modulations in two-way relaying MIMO systems are analyzed. More exactly, the pair wise probability (PEP) is used to evaluate the error performance based on the CPM signal matrix, which is calculated in terms of Laurent expression. Since the channels subject to two terminal nodes share common antennas at relay node R in multiple-access scheme, we revise the JTRAS algorithm and compare it to existing algorithm via simulation. Finally, the error performances for various schemes of antenna selection are simulated and compared to the analysis in this paper.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.11
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• pp.73-81
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• 2016

In general, infrared images have less sharpness and image details than visible images. So, the prior image upscaling methods are not effective in the infrared images. In order to solve this problem, this paper proposes an algorithm which initially up-scales an input infrared (IR) image by using adaptive dynamic range encoding (ADRC)-based super-resolution (SR) method, and then fuses the result with the corresponding visible images. The proposed algorithm consists of a up-scaling phase and a fusion phase. First, an input IR image is up-scaled by the proposed ADRC-based SR algorithm. In the dictionary learning stage of this up-scaling phase, so-called 'pre-emphasis' processing is applied to training-purpose high-resolution images, hence better sharpness is achieved. In the following fusion phase, high-frequency information is extracted from the visible image corresponding to the IR image, and it is adaptively weighted according to the complexity of the IR image. Finally, a up-scaled IR image is obtained by adding the processed high-frequency information to the up-scaled IR image. The experimental results show than the proposed algorithm provides better results than the state-of-the-art SR, i.e., anchored neighborhood regression (A+) algorithm. For example, in terms of just noticeable blur (JNB), the proposed algorithm shows higher value by 0.2184 than the A+. Also, the proposed algorithm outperforms the previous works even in terms of subjective visual quality.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.3
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• pp.109-116
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• 2003

In this paper. we Propose an UXGA class LCD controller for controlling the LCD panel. The proposed controller supports the full screen display using GCD between input and output resolutions. The proposed LCD controller includes the motion detector based on median filter which can detect the motion of input image for the enhancement of a image quality. Also, it divides the motion into 3 stages such as still, semi-moving and moving, and uses the different interpolation algorithms according to the degree of motion. In order to evaluate the performance of the proposed interpolation algorithm, we use PSNR method and compare the conventional algorithm by using computer simulation. For the proposed motion detection algorithm, we use a visual verification and the estimation of pixel changes. The proposed LCD controller has been designed and verified by VHDL. It has been synthesized using Xilinx VirtexE FPGA.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.4
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• pp.360-367
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• 2002

The machine-part group formation is to group the sets of parts having similar processing requirements into part families, and the sets of machines needed to process a particular part family into machine cells. The purpose of this study is to develop a two-phase machine-part group formation algorithm based on Self-Organizing Maps (SOM). In phase I, it forms machine cells from the machine-part incidence matrix by means of SOM whose output layer is one-dimension and the number of output nodes is the twice as many as the number of input nodes in order to spread out the input vectors. In phase II, it generates part families which are assigned to machine cells by means of machine ratio related with processing part and it gives machine-part group formation. The proposed algorithm performs remarkably well in comparison with many well-known algorithms for the machine-part group formation problems.

• Journal of Communications and Networks
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• v.8 no.3
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• pp.290-296
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• 2006

In this paper, a generalized blind adaptive algorithm is introduced for multi-user detection of direct sequence code division multiple access (OS-COMA) wireless communication systems. The main property of the proposed algorithm is its ability to resolve the multipath fading channel resulting in inter symbol interference (ISI) as well as multiple access interference (MAI). Other remarkable properties are its low complexity and mitigation to the near-far problem as well as its insensitivity to asynchronous transmission. The proposed system is based on the minimization of the output energy and convergence to the minimum mean square error (MMSE) detector. It is blind in the sense that it needs no knowledge of the other users' signatures, only the intended user signature and timing are required. Furthermore, the convergence of the minimum output energy (MOE) detector to the MMSE detector is analytically proven in case of M-ary PSK. Depicted results show that the performance of the generalized system dominates those previously considered. Further improvements are obtained when multiple input multiple output (MIMO) technique is employed.