• 제목/요약/키워드: optimal rate of convergence

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커널 회귀함수 추정에서 점근최적인 평활량의 선택에 관한 연구 (Asymptotic optimal bandwidth selection in kernel regression function estimation)

  • 석경하;김대학
    • Journal of the Korean Data and Information Science Society
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    • 제9권1호
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    • pp.19-27
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    • 1998
  • 본 논문에서는 커널 회귀함수의 추정방법에서 최적수렴율 $n^{-1/2}$을 가지는 평활량을 선택하는 방법에 대한 연구를 고려하였다. 이러한 평활량의 선택을 위하여 먼저 평활량의 수행측도인 기대평균제곱오차의 근사값을 4차항까지 테일러 급수전개를 하고 그 전개식을 최소화하는 평활량을 고려하였다. 이때 이 평활량이 포함하고 있는 미지의 범함수를 높은 차수의 커널함수를 이용하여 더욱 정확히 추정할 수 있음을 제안한다. 또한 이렇게 구한 평활량과 최적 평활량과의 상대적 수렴율이 $n^{-1/2}$가 됨을 보였다.

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Blind adaptive receiver for uplink multiuser massive MIMO systems

  • Shin, Joonwoo;Seo, Bangwon
    • ETRI Journal
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    • 제42권1호
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    • pp.26-35
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    • 2020
  • Herein, we consider uplink multiuser massive multiple-input multiple-output systems when multiple users transmit information symbols to a base station (BS) by applying simple space-time block coding (STBC). At the BS receiver, two detection filters for each user are used to detect the STBC information symbols. One of these filters is for odd-indexed symbols and the other for even-indexed symbols. Using constrained output variance metric minimization, we first derive a special relation between the closed-form optimal solutions for the two detection filters. Then, using the derived special relation, we propose a new blind adaptive algorithm for implementing the minimum output variance-based optimal filters. In the proposed adaptive algorithm, filter weight vectors are updated only in the region satisfying the special relation. Through a theoretical analysis of the convergence speed and a computer simulation, we demonstrate that the proposed scheme exhibits faster convergence speed and lower steady-state bit error rate than the conventional scheme.

Asymptotic Characteristics of MSE-Optimal Scalar Quantizers for Generalized Gamma Sources

  • 이재건;나상신
    • 한국통신학회논문지
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    • 제37권5A호
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    • pp.279-289
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    • 2012
  • Characteristics, such as the support limit and distortions, of minimum mean-squared error (MSE) N-level uniform and nonuniform scalar quantizers are studied for the family of the generalized gamma density functions as N increases. For the study, MSE-optimal scalar quantizers are designed at integer rates from 1 to 16 bits/sample, and their characteristics are compared with corresponding asymptotic formulas. The results show that the support limit formulas are generally accurate. They also show that the distortion of nonuniform quantizers is observed to converge to the Panter-Dite asymptotic constant, whereas the distortion of uniform quantizers exhibits slow or even stagnant convergence to its corresponding Hui-Neuhoff asymptotic constant at the studied rate range, though it may stay at a close proximity to the asymptotic constant for the Rayleigh and Laplacian pdfs. Additional terms in the asymptote result in quite considerable accuracy improvement, making the formulas useful especially when rate is 8 or greater.

QoS-Guaranteed Slot Allocation Algorithm for Efficient Medium Access in HR-WPAN

  • Sung, Jung-Sik;Lee, Hyunjeong;Kang, Tae-Gyu;Huh, Jaedoo
    • ETRI Journal
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    • 제37권6호
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    • pp.1242-1250
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    • 2015
  • It is very important to provide a parameterized quality of service (QoS) using traffic specification (TSPEC), such as mean data rate, maximum burst size, and peak data rate, when packets from the application layer need to be transmitted with guaranteed services in a high-rate wireless personal area network (HR-WPAN). As medium resources are limited, the optimal medium time required for each device needs to be estimated to share the resources efficiently among devices. This paper proposes a variable-service interval-based resource allocation algorithm to efficiently make a reservation of medium resources based on a parameterized QoS. In other words, the proposed algorithm calculates the number of medium access slots (MASs) based on TSPEC, local resources, and local conditions and determines suitable locations for the MASs within a superframe to accommodate more devices. The simulation results show that the proposed algorithm can accommodate more devices and has greater than 10% resource allocation efficiency in an HR-WPAN compared to existing schemes.

가변학습율과 온라인모드를 이용한 개선된 EBP 알고리즘 (Improved Error Backpropagation by Elastic Learning Rate and Online Update)

  • Lee, Tae-Seung;Park, Ho-Jin
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2004년도 봄 학술발표논문집 Vol.31 No.1 (B)
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    • pp.568-570
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    • 2004
  • The error-backpropagation (EBP) algerithm for training multilayer perceptrons (MLPs) is known to have good features of robustness and economical efficiency. However, the algorithm has difficulty in selecting an optimal constant learning rate and thus results in non-optimal learning speed and inflexible operation for working data. This paper Introduces an elastic learning rate that guarantees convergence of learning and its local realization by online upoate of MLP parameters Into the original EBP algorithm in order to complement the non-optimality. The results of experiments on a speaker verification system with Korean speech database are presented and discussed to demonstrate the performance improvement of the proposed method in terms of learning speed and flexibility fer working data of the original EBP algorithm.

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On the Characteristics of MSE-Optimal Symmetric Scalar Quantizers for the Generalized Gamma, Bucklew-Gallagher, and Hui-Neuhoff Sources

  • 이재건;나상신
    • 한국통신학회논문지
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    • 제40권7호
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    • pp.1217-1233
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    • 2015
  • The paper studies characteristics of the minimum mean-square error symmetric scalar quantizers for the generalized gamma, Bucklew-Gallagher and Hui-Neuhoff probability density functions. Toward this goal, asymptotic formulas for the inner- and outermost thresholds, and distortion are derived herein for nonuniform quantizers for the Bucklew-Gallagher and Hui-Neuhoff densities, parallelling the previous studies for the generalized gamma density, and optimal uniform and nonuniform quantizers are designed numerically and their characteristics tabulated for integer rates up to 20 and 16 bits, respectively, except for the Hui-Neuhoff density. The assessed asymptotic formulas are found consistently more accurate as the rate increases, essentially making their asymptotic convergence to true values numerically acceptable at the studied bit range, except for the Hui-Neuhoff density, in which case they are still consistent and suggestive of convergence. Also investigated is the uniqueness problem of the differentiation method for finding optimal step sizes of uniform quantizers: it is observed that, for the commonly studied densities, the distortion has a unique local minimizer, hence showing that the differentiation method yields the optimal step size, but also observed that it leads to multiple solutions to numerous generalized gamma densities.

EMPIRICAL BAYES ESTIMATION OF RESIDUAL SURVIVAL FUNCTION AT AGE

  • Liang, Ta-Chen
    • Journal of the Korean Statistical Society
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    • 제33권2호
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    • pp.191-202
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    • 2004
  • The paper considers nonparametric empirical Bayes estimation of residual survival function at age t using a Dirichlet process prior V(a). Empirical Bayes estimators are proposed for the case where both the function ${\alpha}$(0, $\chi$] and the size a(R$\^$+/) are unknown. It is shown that the proposed empirical Bayes estimators are asymptotically optimal at a rate n$\^$-1/, where n is the number of past data available for the present estimation problem. Therefore, the result of Lahiri and Park (1988) in which a(R$\^$+/) is assumed to be known and a rate n$\^$-1/ is achieved, is extended to a(R$\^$+/) unknown case.

연비개선 및 소음저감을 위한 지로터 최적설계 (타원 1-타원형 인벌루트-타원2) (Optimal Design of Gerotor (Ellipse1-Elliptical Involute-Ellipse2 Combined Lobe Shape) for Improving Fuel Efficiency and Reducing Noise)

  • 곽효서;이승환;김철
    • 한국정밀공학회지
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    • 제33권11호
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    • pp.927-935
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    • 2016
  • A gerotor is suitable for miniature manufacturing because it has a high discharge per cycle and a simple structure, while also being widely used as lubrication oil of engines and the hydraulic source of automatic transmission. In the automobile industry, it has been necessary to continuously improve the flow rate and noise of internal gear pumps for better fuel efficiency through optimal gerotor design. In this study, to obtain an optimal gerotor with an ellipse-elliptical involute-ellipse combined lobe shape, an automatic program was developed for calculating performance parameters and drawing a gerotor profile. An oil pump was assembled with the optimal gerotor together with the port used at the actual field and CFD analysis was performed on this assembly using Ansys-CFX. A performance test for the oil pump was carried out and showed good agreement with the results obtained from the theoretical analysis and the CFD analysis.

Performance Analysis of SyncML Server System Using Stochastic Petri Nets

  • Lee, Byung-Yun;Lee, Gil-Haeng;Choi, Hoon
    • ETRI Journal
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    • 제26권4호
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    • pp.360-366
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    • 2004
  • Synchronization Markup Language (SyncML) is a specification of a common data synchronization framework for synchronizing data on networked devices. SyncML is designed for use between mobile devices that are intermittently connected to a network and network services that are continuously available on the network. We have designed and developed a data synchronization system based on the SyncML protocol and evaluated the throughput of the system using the stochastic Petri nets package (SPNP) and analyzed the relationship between the arrival rate and the system resources. Using this model, we evaluate various performance measures in different situations, and we estimate the relationship between the arrival rate and the system resources. From the results, we can estimate the optimal amount of resources due to the arrival rate before deploying the developed system.

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인공지능 기반 객체 인식을 위한 최적 학습모델 구축 방안에 관한 연구 (A Study on How to Build an Optimal Learning Model for Artificial Intelligence-based Object Recognition)

  • 양환석
    • 융합보안논문지
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    • 제23권5호
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    • pp.3-8
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    • 2023
  • 4차 산업혁명으로 많은 산업 분야에 커다란 변화가 일어나고 있으며, 그중에서도 인공지능을 활용한 융합기술에 활발한 연구가 진행되고 있다. 그중에서도 인공지능을 활용한 객체 인식과 인식 결과를 활용한 디지털 전환(Digital Transformation) 분야에서 그 요구가 나날이 증가하고 있다. 본 논문에서는 이미지내에 글자, 심볼, 선을 정확하게 인식하고 인식 결과를 시뮬레이션에 활용할 수 있도록 표준화 포맷의 파일로 저장하기 위해 최적의 학습모델 구축 방법을 제안하였다. 이미지내 글자, 심볼, 선을 인식하기 위하여 인식 대상별 특성을 분석한 후 최적의 인식 기법을 선택하였다. 그다음으로 인식 대상별 인식률을 향상시키기 위하여 최적의 학습 모델 구축 방안을 제안하였다. 글자, 심볼, 선 인식의 순서와 가중치를 다르게 설정하여 인식 결과를 확인하였으며, 인식 후처리에 대한 방안도 마련하였다. 최종적인 인식 결과는 시뮬레이션 등 다양한 처리에 활용될 수 있는 표준화 포맷으로 저장하였다. 본 논문에서 제안한 최적의 학습 모델 구축에 대한 우수한 성능은 실험을 통해 확인할 수 있었다.