• Title/Summary/Keyword: Multi-step optimization

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Synchronization performance optimization using adaptive bandwidth filter and average power controller over DTV system (DTV시스템에서 평균 파워 조절기와 추정 옵셋 변화율에 따른 대역폭 조절 필터를 이용한 동기 성능 최적화)

  • Nam, Wan-Ju;Lee, Sung-Jun;Sohn, Sung-Hwan;Kim, Jae-Moung
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.5
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    • pp.45-53
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    • 2007
  • To recover transmitted signal perfectly at DTV receiver, we have to acquire carrier frequency synchronization to compensate pilot signal which located in wrong position and rotated phase. Also, we need a symbol timing synchronization to compensate sampling timing error. Conventionally, to synchronize symbol timing, we use Gardner's scheme which used in multi-level signal. Gardner's scheme is well known for its sampling the timing error signal from every symbol and it makes easy to detect and keep timing sync in multi-path channel. In this paper, to discuss the problem when the received power level is out of range and we cannot get synchronization information. With this problem, we use 2 step procedures. First, we put a received signal power compensation block before Garder's timing error detector. Second, adaptive loop filter to get a fast synchronization information and averaging loop filter's output value to reduce the amount of jitter after synchronization in PLL(Phased Locked Loop) circuit which is used to get a carrier frequency synchronization and symbol timing synchronization. Using the averaging value, we can estimate offset. Based on offset changing ratio, we can adapt adaptive loop filter to carrier frequency and symbol timing synchronization circuit.

An integrated framework of security tool selection using fuzzy regression and physical programming (퍼지회귀분석과 physical programming을 활용한 정보보호 도구 선정 통합 프레임워크)

  • Nguyen, Hoai-Vu;Kongsuwan, Pauline;Shin, Sang-Mun;Choi, Yong-Sun;Kim, Sang-Kyun
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.11
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    • pp.143-156
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    • 2010
  • Faced with an increase of malicious threats from the Internet as well as local area networks, many companies are considering deploying a security system. To help a decision maker select a suitable security tool, this paper proposed a three-step integrated framework using linear fuzzy regression (LFR) and physical programming (PP). First, based on the experts' estimations on security criteria, analytic hierarchy process (AHP) and quality function deployment (QFD) are employed to specify an intermediate score for each criterion and the relationship among these criteria. Next, evaluation value of each criterion is computed by using LFR. Finally, a goal programming (GP) method is customized to obtain the most appropriate security tool for an organization, considering a tradeoff among the multi-objectives associated with quality, credibility and costs, utilizing the relative weights calculated by the physical programming weights (PPW) algorithm. A numerical example provided illustrates the advantages and contributions of this approach. Proposed approach is anticipated to help a decision maker select a suitable security tool by taking advantage of experts' experience, with noises eliminated, as well as the accuracy of mathematical optimization methods.

DNA Sequence Design using $\varepsilon$ -Multiobjective Evolutionary Algorithm ($\varepsilon$-다중목적함수 진화 알고리즘을 이용한 DNA 서열 디자인)

  • Shin Soo-Yong;Lee In-Hee;Zhang Byoung-Tak
    • Journal of KIISE:Software and Applications
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    • v.32 no.12
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    • pp.1217-1228
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    • 2005
  • Recently, since DNA computing has been widely studied for various applications, DNA sequence design which is the most basic and important step for DNA computing has been highlighted. In previous works, DNA sequence design has been formulated as a multi-objective optimization task, and solved by elitist non-dominated sorting genetic algorithm (NSGA-II). However, NSGA-II needed lots of computational time. Therefore, we use an $\varepsilon$- multiobjective evolutionarv algorithm ($\varepsilon$-MOEA) to overcome the drawbacks of NSGA-II in this paper. To compare the performance of two algorithms in detail, we apply both algorithms to the DTLZ2 benchmark function. $\varepsilon$-MOEA outperformed NSGA-II in both convergence and diversity, $70\%$ and $73\%$ respectively. Especially, $\varepsilon$-MOEA finds optimal solutions using small computational time. Based on these results, we redesign the DNA sequences generated by the previous DNA sequence design tools and the DNA sequences for the 7-travelling salesman problem (TSP). The experimental results show that $\varepsilon$-MOEA outperforms the most cases. Especially, for 7-TSP, $\varepsilon$-MOEA achieves the comparative results two tines faster while finding $22\%$ improved diversity and $92\%$ improved convergence in final solutions using the same time.