• Title/Summary/Keyword: margin adaptive

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ELIMINATION OF BIAS IN THE IIR LMS ALGORITHM (IIR LMS 알고리즘에서의 바이어스 제거)

  • Nam, Seung-Hyon;Kim, Yong-Hoh
    • The Journal of Natural Sciences
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    • v.8 no.1
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    • pp.5-15
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    • 1995
  • The equation error formulation in the adaptive IIR filtering provides convergence to a global minimum regardless a local minimum with a large stability margin. However, the equation error formulation suffers from the bias in the coefficient estimates. In this paper, a new algorithm, which does not require a prespecification of the noise variance, is proposed for the equation error formulation. This algorithm is based on the equation error smoothing and provides an unbiased parameter estimate in the presence of white noise. Through simulations, it is demonstrated that the algorithm eliminates the bias in the parameter estimate while retaining good properties of the equation error formulation such as fast convergence speed and the large stability margin.

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Adaptive Attention Annotation Model: Optimizing the Prediction Path through Dependency Fusion

  • Wang, Fangxin;Liu, Jie;Zhang, Shuwu;Zhang, Guixuan;Zheng, Yang;Li, Xiaoqian;Liang, Wei;Li, Yuejun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.9
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    • pp.4665-4683
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    • 2019
  • Previous methods build image annotation model by leveraging three basic dependencies: relations between image and label (image/label), between images (image/image) and between labels (label/label). Even though plenty of researches show that multiple dependencies can work jointly to improve annotation performance, different dependencies actually do not "work jointly" in their diagram, whose performance is largely depending on the result predicted by image/label section. To address this problem, we propose the adaptive attention annotation model (AAAM) to associate these dependencies with the prediction path, which is composed of a series of labels (tags) in the order they are detected. In particular, we optimize the prediction path by detecting the relevant labels from the easy-to-detect to the hard-to-detect, which are found using Binary Cross-Entropy (BCE) and Triplet Margin (TM) losses, respectively. Besides, in order to capture the inforamtion of each label, instead of explicitly extracting regional featutres, we propose the self-attention machanism to implicitly enhance the relevant region and restrain those irrelevant. To validate the effective of the model, we conduct experiments on three well-known public datasets, COCO 2014, IAPR TC-12 and NUSWIDE, and achieve better performance than the state-of-the-art methods.

Calculating the collapse margin ratio of RC frames using soft computing models

  • Sadeghpour, Ali;Ozay, Giray
    • Structural Engineering and Mechanics
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    • v.83 no.3
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    • pp.327-340
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    • 2022
  • The Collapse Margin Ratio (CMR) is a notable index used for seismic assessment of the structures. As proposed by FEMA P695, a set of analyses including the Nonlinear Static Analysis (NSA), Incremental Dynamic Analysis (IDA), together with Fragility Analysis, which are typically time-taking and computationally unaffordable, need to be conducted, so that the CMR could be obtained. To address this issue and to achieve a quick and efficient method to estimate the CMR, the Artificial Neural Network (ANN), Response Surface Method (RSM), and Adaptive Neuro-Fuzzy Inference System (ANFIS) will be introduced in the current research. Accordingly, using the NSA results, an attempt was made to find a fast and efficient approach to derive the CMR. To this end, 5016 IDA analyses based on FEMA P695 methodology on 114 various Reinforced Concrete (RC) frames with 1 to 12 stories have been carried out. In this respect, five parameters have been used as the independent and desired inputs of the systems. On the other hand, the CMR is regarded as the output of the systems. Accordingly, a double hidden layer neural network with Levenberg-Marquardt training and learning algorithm was taken into account. Moreover, in the RSM approach, the quadratic system incorporating 20 parameters was implemented. Correspondingly, the Analysis of Variance (ANOVA) has been employed to discuss the results taken from the developed model. Additionally, the essential parameters and interactions are extracted, and input parameters are sorted according to their importance. Moreover, the ANFIS using Takagi-Sugeno fuzzy system was employed. Finally, all methods were compared, and the effective parameters and associated relationships were extracted. In contrast to the other approaches, the ANFIS provided the best efficiency and high accuracy with the minimum desired errors. Comparatively, it was obtained that the ANN method is more effective than the RSM and has a higher regression coefficient and lower statistical errors.

Control-structure interaction in piezoelectric deformable mirrors for adaptive optics

  • Wang, Kainan;Alaluf, David;Mokrani, Bilal;Preumont, Andre
    • Smart Structures and Systems
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    • v.21 no.6
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    • pp.777-791
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    • 2018
  • This paper discusses the shape control of deformable mirrors for Adaptive Optics in the dynamic range. The phenomenon of control-structure interaction appears when the mirror becomes large, lowering the natural frequencies $f_i$, and the control bandwidth $f_c$ increases to improve the performance, so that the condition $f_c{\ll}f_i$ is no longer satisfied. In this case, the control system tends to amplify the response of the flexible modes and the system may become unstable. The main parameters controlling the phenomenon are the frequency ratio $f_c/f_i$ and the structural damping ${\zeta}$. Robustness tests are developed which allow to evaluate a lower bound of the stability margin. Various passive and active strategies for damping augmentation are proposed and tested in simulation.

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.

Graph Connectivity-free Consensus Algorithm for State-coupled Linear Multi-agent Systems: Adaptive Approach (적응 제어를 이용하여 그래프 연결성을 배제시킨 선형 다개체 시스템의 상태변수 일치 알고리듬)

  • Kim, Ji-Su;Kim, Hong-Keun;Shim, Hyung-Bo;Back, Ju-Hoon
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.7
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    • pp.617-621
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    • 2012
  • This paper studies asymptotic consensus problem for linear multi-agent systems. We propose a distributed state feedback control algorithm for solving the problem under fixed and undirected network communication. In contrast with the conventional algorithms that use global information (e.g., graph connectivity), the proposed algorithm only uses local information from neighbors. The principle for achieving asymptotic consensus is that, for each agent, a distributed update law gradually increases the coupling gain of LQR-type feedback and thus, the overall stability of the multi-agent system is recovered by the gain margin of LQR.

Widely Tunable Adaptive Resolution-controlled Read-sensing Reference Current Generation for Reliable PRAM Data Read at Scaled Technologies

  • Park, Mu-hui;Kong, Bai-Sun
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.17 no.3
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    • pp.363-369
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    • 2017
  • Phase-change random access memory (PRAM) has been emerged as a potential memory due to its excellent scalability, non-volatility, and random accessibility. But, as the cell current is reducing due to cell size scaling, the read-sensing window margin is also decreasing due to increased variation of cell performance distribution, resulting in a substantial loss of yield. To cope with this problem, a novel adaptive read-sensing reference current generation scheme is proposed, whose trimming range and resolution are adaptively controlled depending on process conditions. Performance evaluation in a 58-nm CMOS process indicated that the proposed read-sensing reference current scheme allowed the integral nonlinearity (INL) to be improved from 10.3 LSB to 2.14 LSB (79% reduction), and the differential nonlinearity (DNL) from 2.29 LSB to 0.94 LSB (59% reduction).

Human Drivers' Driving Pattern Analysis and An Adaptive Cruise Control Strategy (운전자 주행 패턴 분석 및 차량의 순항제어 기법)

  • 문일기;이경수
    • Transactions of the Korean Society of Automotive Engineers
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    • v.12 no.4
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    • pp.191-197
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    • 2004
  • This paper presents experimental results for human drivers' driving patterns and an Adaptive Cruise Control(ACC) strategy. Analyses have shown that female drivers' driving characteristic values such as time-gap and minimum clearance are larger than those of male drivers'. Human drivers tend to have more clearance margins at high speed than at low speed. At low speed, drivers are much more sensitive to the desired clearance than at high speed. A multi-vehicle detection method is presented to improve ride quality of an ACC. Simulation results have shown that the proposed ACC can provide superior performance compared to the ACC strategy which uses a single-vehicle detection method.

HEARING AND HOWLING SUPPRESSION BY ADAPTIVE FEEDBACK CANCELLATION WITH FREQUENCY COMPRESSION

  • Harry Alfonso L. Joson;futoshi Asano;Yoiti Suzuki;Toshio Sone
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1994.06a
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    • pp.919-924
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    • 1994
  • The use of adaptive feedback cancellation to prevent howling requires a reference signal that is correlated with the feedback signal by is not correlated with the input signal. Such a signal is hard to obtain in hearing aids. In this paper, the use fo frequency compression to decorrelate the output signal with input signal for use as reference is presented. Performance evaluation results indicate that with the proper choice of system parameters, the use of this system can provide a significant increase in howling margin with minimal deterioration in output signal quality.

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Dynamic Reserve Estimating Method with Consideration of Uncertainties in Supply and Demand (수요와 공급의 불확실성을 고려한 시간대별 순동예비력 산정 방안)

  • Kwon, Kyung-Bin;Park, Hyeon-Gon;Lyu, Jae-Kun;Kim, Yu-Chang;Park, Jong-Keun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.62 no.11
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    • pp.1495-1504
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    • 2013
  • Renewable energy integration and increased system complexities make system operator maintain supply and demand balance harder than before. To keep the grid frequency in a stable range, an appropriate spinning reserve margin should be procured with consideration of ever-changing system situation, such as demand, wind power output and generator failure. This paper propose a novel concept of dynamic reserve, which arrange different spinning reserve margin depending on time. To investigate the effectiveness of the proposed dynamic reserve, we developed a new short-term reliability criterion that estimates the probability of a spinning reserve shortage events, thus indicating grid frequency stability. Uncertainties of demand forecast error, wind generation forecast error and generator failure have been modeled in probabilistic terms, and the proposed spinning reserve has been applied to generation scheduling. This approach has been tested on the modified IEEE 118-bus system with a wind farm. The results show that the required spinning reserve margin changes depending on the system situation of demand, wind generation and generator failure. Moreover the proposed approach could be utilized even in case of system configuration change, such as wind generation extension.