• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.9
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• pp.1095-1103
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• 1992

An approach to fuse the fuzzy inference system which is able to deal with imprecise and uncertain information and genetic algorithms which display the excellent robustness in complex optimization problems is presented in this paper. In order to combine genetic algorithms and fuzzy inference engine effectively the new reasoning method is suggested. The efficient identification method of fuzzy rules is proposed through the adjustment of search areas of genetic algorithms. The feasibilty of the proposed approach is evaluated through simulation.

• The Transactions of the Korea Information Processing Society
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• v.5 no.9
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• pp.2447-2456
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• 1998

Edge detection in the presence of noise is a well-known problem. this pper atempts to implement edge detection algorithms using fuzzy reasoning of fuzzy membership models. It examines an application-motived approach for solving the problem. Our approach is divided into three stages; fitering, segmentation and tracing. Filtering removes the noise from the original image and segmentation determines the edges and deects them. Finally, tracing assembles the edges into the related structure. Proposed method can be used effectively on these procedures by using fuzzy reasoning based on fuzzy models. In is compared with the previous edge detectio algorithms with fvorable results. Simulation results of the research are presented and discussed.

• Journal of KIISE:Information Networking
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• v.29 no.6
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• pp.625-634
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• 2002

Cryptography is the methods of making and using secret writing that is necessary to keep messages private between two parties. Cryptography is compute-intensive algorithm and needs cpu resource excessively. To solve these problems, there exists hardware approach that implements cryptographic algorithm with hardware chip. In this paper, we presents the design and implementation of cryptographic hardware and compares its performance with software cryptographic algorithms. The experimental result shows that the hardware approach causes high I/O overheads when it transmits data between cryptographic board and host cpu. Hence, low complexity cryptographic algorithms such as DES does not improve the performance. But high complexity cryptographic algorithms such as Triple DES improve the performance with a high rate, roughly from two times to Sour times.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.139-145
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• 2015

This paper compare the VSCA (Variable stepsize Square Contour Algorithm) and VSDA (Variable stepsize Square contour Decision directed Algorithm) adaptive equalization algorithm that is used for the minimization of the intersymbol interference which occurs in the time dispersive channel for the transmission of 16-QAM signal.. In the SCA, it is possible to compensates the amplitude and phase in the received signal that are mixed with the intersymbol interference by the constellatin dependent constant by using the 2nd order statistics of the transmitted signal. But in the VSCA and VSDA, it is possible to the improving the equalization performance by varing the stepsize using the concept of distance adjusted approach for constellation matching. We compare the performance of the VSCA and VSDA algorithm by the computer simulation. For this, the equalizer output signal constellation, residual isi, maximum distortion and MSE were used in the performace index. As a result of computer simulation, the VSCA algorithm has better than the VSDA in every performance index.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.2269-2275
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• 2010

The performance of Genetic Algorithms (GA) is affected by various factors such as parameters, genetic operators and strategies. The traditional approach with random initial population is efficient however the whole initial population may contain many infeasible solutions. Thus it would take a long time for GA to produce a good solution. The GA have been modified in various ways to achieve faster convergence and it was particularly recognized by researchers that initial population greatly affects the performance of GA. This study proposes modified GA with sorted initial population and applies it to solving Travelling Salesman Problem (TSP). Normally, the bigger the initial the population is the more computationally expensive the calculation becomes with each generation. New approach allows reducing the size of the initial problem and thus achieve faster convergence. The proposed approach is tested on a simulator built using object-oriented approach and the test results prove the validity of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.3B
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• pp.305-313
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• 2004

Group multicast refers to the kind of multicast in which every member of a group is allowed to transmit data to the group. The goal of routing algorithms for group multicast is to construct a set of low cost multicast trees including all the group members with QoS (e.g., bandwidth) constraint. There have been several algorithms proposed: source tree and shared tree approaches. However, the latter approach has a low success rate in constructing a shared multicast tree, and the former approach suffers from high control overhead and low scalability as stoup size increases. In this paper, we present a heuristic algorithm which varies the number of multicast trees according to the network load. The simulation results show not only that our algorithm outperforms the shared tree approach in terms of the success rate, but also that it has lower control overhead than the source tree approach while guaranteeing the same success rate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.999-1001
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• 2015

CW Doppler radar is capable of giving the relative velocity of an object using the Doppler effect. When detecting more than an object, frequency domain analysis is needed using CW Doppler radar and FFT. Even though the number of objects and velocities can be obtained within the frequency domain, there is a disadvantage that it is difficult to assess information on approach or deviation of an object. When detecting more than an object using FFT, this study suggests an algorithm for efficiently assessing information about approach or deviation of objects within the frequency domain. The proposed algorithm divides sections into real and imaginary numbers in the frequency domain, and then determines deviation if the total sum of the amplitudes of each frequency is on the left side and approach if the total sum of the amplitudes is on the right side.

• Journal of Satellite, Information and Communications
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• v.5 no.1
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• pp.32-37
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• 2010

The algorithm of multiple channel signal processing requires the flexibility of variable frequency band, efficient allocation of transmission power, and flexible frequency band reallocation to satisfy various service types which requires different transmission rates and frequency band. There are three methods including per-channel approach, multiple tree approach, and block approach performing frequency band reallocation method by channelization and dechannelization in the multiple-channel signal. This paper proposes an improved per-channel approach for converting the frequency band of multiple carrier signals efficiently. The proposed algorithm performs decimation and interpolation using CIC(cascaded integrator comb filter), half-band filter, and FIR filter. In addition, it performs filtering of each sub-channel, and reallocates channel band through FIR low-pass filter in the multiple-channel signal. The computer simulation result shows that the perfect reconstruction of output signal and the flexible frequency band reallocation is performed efficiently by the proposed algorithm.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.73-82
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• 2022

Driver acceptance of autonomous driving is very important. The autonomous driving longitudinal controller, which is one of the factors affecting acceptability, consists of a high-level controller and a low-level controller. The host controller decides the cruise control and the space control according to the situation and creates the required target speed. The sub-controller performs control by creating an acceleration signal to follow the target speed. In this paper, we propose an algorithm to improve the inter-vehicle distance fluctuations that occur in the cruise control and space control switching problems in the host controller. The proposed method is to add an approach algorithm to the cruise control at the time of switching from cruise control to space control so that it is switched to space control at the correct switching distance. Through this, the error was improved from 12m error to 4m, and actual vehicle verification was performed.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.63-82
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• 2007

In this paper, we propose an adaptive hybrid genetic algorithm (ahGA) approach for effectively solving multistage-based scheduling problems in flexible manufacturing system (FMS) environment. The proposed ahGA uses a neighborhood search technique for local search and an adaptive scheme for regulation of GA parameters in order to improve the solution of FMS scheduling problem and to enhance the performance of genetic search process, respectively. In numerical experiment, we present two types of multistage-based scheduling problems to compare the performances of the proposed ahGA with conventional competing algorithms. Experimental results show that the proposed ahGA outperforms the conventional algorithms.