• Journal of the Institute of Electronics Engineers of Korea SC
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• 제40권3호
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• pp.145-151
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• 2003

This study focuses on the hardware implementation of fast and low-complexity multiplier over GF(2$^{m}$ ). Finite field multiplication can be realized in two steps: polynomial multiplication and modular reduction using the irreducible polynomial and we will treat both operation, separately. Polynomial multiplicative operation in this Paper is based on the Permestzi's algorithm, and irreducible polynomial is defined AOP. The realization of the proposed GF(2$^{m}$ ) multipleker-based multiplier scheme is compared to existing multiplier designs in terms of circuit complexity and operation delay time. Proposed multiplier obtained have low circuit complexity and delay time, and the interconnections of the circuit are regular, well-suited for VLSI realization.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 한국퍼지및지능시스템학회 2005년도 추계학술대회 학술발표 논문집 제15권 제2호
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• pp.335-338
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• 2005

로봇 에이전트는 변화하는 환경에서 센서정보를 바탕으로 적절한 행동을 선택하며 동작하는 것이 중요하다. 행동 선택 네트워크는 이러한 환경에서 변화하는 센서정보에 따라 실시간으로 행동을 선택할 수 있다는 점에서, 장시간에 걸친 최적화보다 단시간 내 개선된 효율성에 초점을 맞추어 사용되어 왔다. 하지만 행동 선택 네트워크는 초기 문제에 의존적으로 설계되어 변화하는 환경에 유연하게 대처하지 못한다는 맹점을 가지고 있다. 본 논문에서는 행동 선택 네트워크의 연결을 LCS를 기반으로 진화 학습시켰다. LCS는 유전자 알고리즘을 통해 만들어진 규칙들을 강화학습을 통해 평가하며, 이를 통해 변화하는 환경에 적합한 규칙을 생성한다. 제안하는 모델에서는 LCS의 규칙이 센서정보를 포함한다. 진화가 진행되는 도중 이 규칙들이 모든 센서 정보를 포함하지 못하기 때문에 현재의 센서 정보를 반영하지 못하는 경우가 발생할 수 있다. 본 논문에서는 이를 해결하기 위해 센서정보 별로 개체를 따로 유지하는 방법을 제안한다. 제안하는 방법의 검증을 위해 Webots 시뮬레이터에서 케페라 로봇을 이용해 실험을 하여, 변화하는 환경에서 로봇 에이전트가 학습을 통해 올바른 행동을 선택함을 보였고, 일반LCS를 사용한 것보다 조건별 개체 유지를 통해 더 나은 결과를 보이는 것 또한 확인하였다.

• Journal of Navigation and Port Research
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• 제31권6호
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• pp.531-536
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• 2007

In this paper we present an interpolation-LQ control technique which tunes continuously the controller gain by interpolating the gains of sub-LQ controllers. The proposed controller design technique is applied to the container crane system for simulations. Several cases of simulations are carried out in order to prove the control effectiveness and robustness. The simulation results of the proposed controller are compared with those of LQ controllers. The results showed better control performance than those of LQ controllers.

• Journal of the Korean Institute of Intelligent Systems
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• 제14권2호
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• pp.164-170
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• 2004

This paper proposes a Distributed Autonomous Robotic System(AIS) based on Artificial Immune System(AIS) and Distributed Genetic Algorithm(DGA). The behaviors of robots in the system are divided into global behaviors and local behaviors. The global behaviors are actions to search tasks in environment. These actions are composed of two types: dispersion and aggregation. AIS decides one among above two actions, which robot should select and act on in the global. The local behaviors are actions to execute searched tasks. The robots learn the cooperative actions in these behaviors by the DGA in the local. The proposed system is more adaptive than the existing system at the viewpoint that the robots learn and adapt the changing of tasks.

• Journal of the Korean Institute of Intelligent Systems
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• 제14권6호
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• pp.699-704
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• 2004

This paper proposes a Distributed Autonomous Robotic System(DARS) based on an Artificial Immune System(AIS) and a Classifier System(CS). The behaviors of robots in the system are divided into global behaviors and local behaviors. The global behaviors are actions to search tasks in environment. These actions are composed of two types: aggregation and dispersion. AIS decides one among these two actions, which robot should select and act on in the global. The local behaviors are actions to execute searched tasks. The robots learn the cooperative actions in these behaviors by the CS in the local. The proposed system is more adaptive than the existing system at the viewpoint that the robots learn and adapt the changing of tasks.

• Proceedings of the Korea Contents Association Conference
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• 한국콘텐츠학회 2004년도 춘계 종합학술대회 논문집
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• pp.396-400
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• 2004

In this study, we have proposed the tracking system of single moving object. The tracking system was estimated motion using differential image, and than track the moving object by controlled Pan/Tilt device of camera. Proposed tracking system is devided into image acquisition and preprocessing phase, motion estimation phase and object tracking phase. To estimation the motion, differential image method was used. In the binary differential image, decision of threshold value was used adaptive method. And in grouping the object area, block_based recursive labeling algorithm was used. As a result of experiment, motion of moving object can be estimated. The result of tracking, object was not lost and object was tracked correctly.

• The Journal of the Korea Contents Association
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• 제10권1호
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• pp.59-67
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• 2010

Laboratory works for embedded system courses are usually performed with hardware based experimental kits that equipped with an embedded board and software development tools. Hardware-based kits have demerits such as high initial setup cost, burdensome maintenance, inadaptability to industry evolution, and restricted educational outcomes. This paper proposes using virtual experimental environments to overcome the demerits of hardware-based kits and describes the design and implementation of a simulation-based virtual experimental kit. With ARM's ARMulator, we developed the kit by adding hardware IPs and user interface modules for peripherals. The developed kit is verified with an experimental program that uses all the augmented software modules. We also ported MicroC/OS-II on the virtual experimental kit for real-time OS experiments.

• 전자공학회논문지 IE
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• 제46권2호
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• pp.7-10
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• 2009

This paper presents the implementation of libraries of hardware modules for genetic algorithm using VHDL. Evolvable hardware refers to hardware that can change its architecture and behavior dynamically and autonomously by interacting with its environment. So, it is especially suited to applications where no hardware specifications can be given in advance. Evolvable hardware is based on the idea of combining reconfigurable hardware device with evolutionary computation, such as genetic algorithm. Because of parallel, no function call overhead and pipelining, a hardware genetic algorithm give speedup over a software genetic algorithm. This paper suggests the hardware genetic algorithm for evolvable embedded system chip. That includes simulation results and analysis for several fitness functions. It can be seen that our design works well for the three examples.

• Journal of IKEEE
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• 제19권2호
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• pp.254-259
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• 2015

CABAC is a context-based adaptive binary arithmetic coding method. It increases the encoding efficiency by updating the probability based on the information of the previously coded symbols. Context modeler is a core block of CABAC, which designs a probability model according to the symbol considering statistical correlations. In this paper, an efficient hardware architecture of CABAC context modeler is proposed. The proposed context modeler was designed in Verilog HDL and it was implemented in 0.18 um technology. Its gate count is 29,832 gates including memory. Its operating speed and throughput are 200 MHz and 200 Mbin/s, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제40권2호
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• pp.247-252
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• 2015

Adaptive algorithms based on the criterion of zero-error probability (ZEP) have robustness to impulsive noise and their decision feedback (DF) versions are known to compensate effectively for severe multipath channel distortions. However the ZEP-DF algorithm computes several summation operations at each iteration time for each filter section and this plays an obstacle role in practical implementation. In this paper, the ZEP-DF with recursive gradient estimation (RGE) method is proposed and shown to reduce the computational burden of O(N) to a constant which is independent of the sample size N. Also the weight update of the initial state and the steady state is a continuous process without bringing about any propagation of gradient estimation error in DF structure.