• Title/Summary/Keyword: Adaptive Optimization

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Adaptive Techniques for Joint Optimization of XTC and DFE Loop Gain in High-Speed I/O

  • Oh, Taehyoun;Harjani, Ramesh
    • ETRI Journal
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    • v.37 no.5
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    • pp.906-916
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    • 2015
  • High-speed I/O channels require adaptive techniques to optimize the settings for filter tap weights at decision feedback equalization (DFE) read channels to compensate for channel inter-symbol interference (ISI) and crosstalk from multiple adjacent channels. Both ISI and crosstalk tend to vary with channel length, process, and temperature variations. Individually optimizing parameters such as those just mentioned leads to suboptimal solutions. We propose a joint optimization technique for crosstalk cancellation (XTC) at DFE to compensate for both ISI and XTC in high-speed I/O channels. The technique is used to compensate for between 15.7 dB and 19.7 dB of channel loss combined with a variety of crosstalk strengths from $60mV_{p-p}$ to $180mV_{p-p}$ adaptively, where the transmit non-return-to-zero signal amplitude is a constant $500mV_{p-p}$.

Enhanced Adaptive Beamforming and Null Steering Algorithms in Cognitive Radio System

  • Zhuang, Zhili;Sohn, Sung-Hwan;Kim, Jae-Moung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.11A
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    • pp.822-830
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    • 2009
  • The spectrum efficiency of mobile communication networks can be improved dramatically adopting multiple antennas technologies. In order to guarantee the licensed rights of primary user (PU), the cognitive radio system should perform in a relatively low interference manner when it gets access to the spectrum of licensed networks. In this paper, we explore a uniformly distributed circular antenna array to implement beamforming algorithm that is accomplished by optimization method at the base station of cognitive radio networks, and therefore we can suppress the interference to PU by steering quite low transmission power toward PU and constructing a narrow beam toward cognitive user (CU). By reducing the constraint number of the optimization problem, we also propose a null steering algorithm that steers rather low radiation power toward PU, while the other areas in the same cell are covered by radiation power except the local area around PU. It is pursued to reduce the computation load and enlarge the capacity of cognitive radio networks extremely. The simulation results demonstrate that the proposed algorithms process superior performance.

Cross Layer Optimization for Scalable Video Streaming (효율적인 Scalable Video Streaming을 위한 Cross Layer Optimization)

  • Yoon, Min-Young;Cho, Hee-Young;Suh, Doug-Young
    • Proceedings of the KIEE Conference
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    • 2005.10b
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    • pp.352-354
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    • 2005
  • As further Studies on 4th generation mobile telecommunication are progressed, the importance of a Cross-Layer is being increased. However, it has focused on coordination model only between MAC layer and PHY layer. It is necessary to expand into II' layer and upper layers. In this paper, we introduce a Cross-layer optimization which can be used to transmit video data with effect by managing resources among layers. It can gives further more adaptive method to solve QoS model problem than single layer.

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A Study on Feedrate Optimization System for Cutting Force Optimization (절삭력 최적화를 위한 이송속도 제어 시스템에 관한 연구)

  • 김성진;정영훈;조동우
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2002.10a
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    • pp.135-140
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    • 2002
  • Studies on the optimization of machining process can be divided into two different approaches: off-line feedrate scheduling and adaptive control. Each approach possesses its respective strong and weak points compared to each other. That is, each system can be complementary to the other. In this regard, a combined system, which is a feedrate control system for cutting force optimization, was proposed in this paper to make the best of each approach. Experimental results show that the proposed system could overcome the weak points of two systems.

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Comparative Study on Reliability-Based Topology Optimization (신뢰성 기반 위상최적화에 대한 비교 연구)

  • Cho, Kang-Hee;Hwang, Seung-Min;Park, Jae-Yong;Han, Seog-Young
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.20 no.4
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    • pp.412-418
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    • 2011
  • Reliability-based Topology optimization(RBTO) is to get an optimal design satisfying uncertainties of design variables. Although RBTO based on homogenization and density distribution method has been done, RBTO based on BESO has not been reported yet. This study presents a reliability-based topology optimization(RBTO) using bi-directional evolutionary structural optimization(BESO). Topology optimization is formulated as volume minimization problem with probabilistic displacement constraint. Young's modulus, external load and thickness are considered as uncertain variables. In order to compute reliability index, four methods, i.e., RIA, PMA, SLSV and ADL(adaptive-loop), are used. Reliability-based topology optimization design process is conducted to obtain optimal topology satisfying allowable displacement and target reliability index with the above four methods, and then each result is compared with respect to numerical stability and computing time. The results of this study show that the RBTO based on BESO using the four methods can effectively be applied for topology optimization. And it was confirmed that DLSV and ADL had better numerical efficiency than SLSV. ADL and SLSV had better time cost than DLSV. Consequently, ADL method showed the best time efficiency and good numerical stability.

Optimization of Channel Prediction Algorithm of Return Link ACM for Satellite Communication (위성통신용 적응형 전송기술 리턴링크 채널예측 알고리즘 최적화)

  • Kim, Hyun-Ho;Kim, Guk-Hyun;Ryu, Joon-Gyu;Hong, Sung-Yong
    • Journal of Satellite, Information and Communications
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    • v.10 no.2
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    • pp.19-23
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    • 2015
  • In this paper, we present the return link ACM method to improve the link availability and system throughput for satellite communication service. Also, we describe the optimization of an algorithm for channel prediction using the LMS (Least Mean Square) adaptive filter and the MODCOD (Modulation & Code rate) decision. The simulation results show that the optimized filter taps and step-size of adaptive filter are 2 and 0.00026, respectively. And also confirms the required SNR margin for minimization of MODCOD decision error is 0.3dB.

ECG Identification Method Using Adaptive Weight Based LMSE Optimization (적응적 가중치를 사용한 LMSE 최적화 기반의 심전도 개인 인식 방법)

  • Kim, Seok-Ho;Kang, Hyun-Soo
    • The Journal of the Korea Contents Association
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    • v.15 no.4
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    • pp.1-8
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    • 2015
  • This paper presents a Electrocardiogram(ECG) identification method using adaptive weight based on Least Mean Square Error(LMSE) optimization. With a preprocessing for noise suppression, we extracts the average ECG signal and its standard deviation at every time instant. Then the extracted information is stored in database. ECG identification is achieved by matching an input ECG signal with the information in database. In computing the matching scores, the standard deviation is used. The scores are computed by applying adaptive weights to the values of the input signal over all time instants. The adaptive weight consists of two terms. The first term is the inverse of the standard deviation of an input signal. The second term is the proportional one to the standard deviation between user SAECGs stored in the DB. Experimental results show up to 100% recognition rate for 32 registered people.

Margin Adaptive Optimization in Multi-User MISO-OFDM Systems under Rate Constraint

  • Wei, Chuanming;Qiu, Ling;Zhu, Jinkang
    • Journal of Communications and Networks
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    • v.9 no.2
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    • pp.112-117
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    • 2007
  • In this paper, we focus on the total transmission power minimization problem for downlink beamforming multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems while ensuring each user's QoS requirement. Although the linear integer programming (LIP) solution we formulate provides the performance upper bound of the margin adaptive (MA) optimization problem, it is hard to be implemented in practice due to its high computational complexity. By regarding each user's equivalent channel gain as approximate independent values and using iterative descent method, we present a heuristic MA resource allocation algorithm. Simulation results show that the proposed algorithm efficiently converges to the local optimum, which is very close to the performance of the optimal LIP solution. Compared with existing space division multiple access (SDMA) OFDM systems with or without adaptive resource allocation, the proposed algorithm achieves significant performance improvement by exploiting the frequency diversity and multi-user diversity in downlink multiple-input single-output (MISO) OFDM systems.

Adaptive Sliding Mode Control with Enhanced Optimal Reaching Law for Boost Converter Based Hybrid Power Sources in Electric Vehicles

  • Wang, Bin;Wang, Chaohui;Hu, Qiao;Ma, Guangliang;Zhou, Jiahui
    • Journal of Power Electronics
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    • v.19 no.2
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    • pp.549-559
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    • 2019
  • This paper proposes an adaptive sliding mode control (ASMC) strategy with an enhanced optimal reaching law (EORL) for the robust current tracking control of the boost converter based hybrid power source (HPS) in an electric vehicle (EV). A conventional ASMC strategy based on state observers and the hysteresis control method is used to realize the current tracking control for the boost converter based HPS. Then a novel enhanced exponential reaching law is proposed to improve the ASMC. Moreover, an enhanced exponential reaching law is optimized by particle swarm optimization. Finally, the adaptive control factor is redesigned based on the EORL. Simulations and experiments are established to validate the ASMC strategy with the EORL. Results show that the ASMC strategy with the EORL has an excellent current tracking control effect for the boost converter based HPS. When compared with the conventional ASMC strategy, the convergence time of the ASMC strategy with the EORL can be effectively improved. In EV applications, the ASMC strategy with the EORL can achieve robust current tracking control of the boost converter based HPS. It can guarantee the active and stable power distribution for boost converter based HPS.

Adaptive Control of Robot Manipulator using Neuvo-Fuzzy Controller

  • Park, Se-Jun;Yang, Seung-Hyuk;Yang, Tae-Kyu
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.161.4-161
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    • 2001
  • This paper presents adaptive control of robot manipulator using neuro-fuzzy controller Fuzzy logic is control incorrect system without correct mathematical modeling. And, neural network has learning ability, error interpolation ability of information distributed data processing, robustness for distortion and adaptive ability. To reduce the number of fuzzy rules of the FLS(fuzzy logic system), we consider the properties of robot dynamic. In fuzzy logic, speciality and optimization of rule-base creation using learning ability of neural network. This paper presents control of robot manipulator using neuro-fuzzy controller. In proposed controller, fuzzy input is trajectory following error and trajectory following error differential ...

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