• Title/Summary/Keyword: bounds

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On lower bounds of eigenvalues for self adjoint operators

  • Lee, Gyou-Bong
    • Journal of the Korean Mathematical Society
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    • v.31 no.3
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    • pp.477-492
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    • 1994
  • For the eigenvalue problem of $Au = \lambda u$ where A is considered as a semi-bounded self-adjoint operator on a Hilbert space, we are used to apply two complentary methods finding upper bounds and lower bounds to the eigenvalues. The most popular method for finding upper bounds may be the Rayleigh-Ritz method which was developed in the 19th century while a method for computing lower bounds may be the method of intermediate eigenvalue problems which has been developed since 1950's. In the method of intermediate eigenvalue problems (IEP), we consider the original operator eigenvalue problem as a perturbation of a simpler, resolvable, self-adjoint eigenvalue problem, called a base problem, that gives rough lower bounds.

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New Upper Bounds for the CALE: A Singular Value Decomposition Approach

  • Savov, Svetoslav G.;Popchev, Ivan P.
    • International Journal of Control, Automation, and Systems
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    • v.6 no.2
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    • pp.288-294
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    • 2008
  • Motivated by the fact that upper solution bounds for the continuous Lyapunov equation are valid under some very restrictive conditions, an attempt is made to extend the set of Hurwitz matrices for which such bounds are applicable. It is shown that the matrix set for which solution bounds are available is only a subset of another stable matrices set. This helps to loosen the validity restriction. The new bounds are illustrated by examples.

Performance bounds of optimal FIR filter-under modeling uncertainty (모델 불확실성에 대한 초적 FIR 필터의 성능한계)

  • 유경상;권오규
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.64-69
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    • 1993
  • In this paper we present the performance bounds of the optimal FIR filter in continuous time systems with modeling uncertainty. The performance measure bounds are calculated from the estimation error covariance bounds of the optimal FIR filter and the suboptimal FIR filter. Performance error bounds range are expressed by the upper bounds on the estimation error covariance difference between the real and nominal values in case of the systems with noise uncertainty or model uncertainty. The performance bounds of the systems are derived on the assumption that the system uncertainty and the estimation error covariance are imperfectly known a priori. The estimation error bounds of the optimal FIR filter is compared with those of the Kalman filter via a numerical example applied to the estimation of the motion of an aircraft carrier at sea, which shows the former has better performances than the latter.

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Estimating BP Decoding Performance of Moderate-Length Irregular LDPC Codes with Sphere Bounds

  • Chung, Kyu-Hyuk
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.7C
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    • pp.594-597
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    • 2010
  • This paper estimates belief-propagation (BP) decoding performance of moderate-length irregular low-density parity-check (LDPC) codes with sphere bounds. We note that for moderate-length($10^3{\leq}N{\leq}4\times10^3$) irregular LDPC codes, BP decoding performance, which is much worse than maximum likelihood (ML) decoding performance, is well matched with one of loose upper bounds, i.e., sphere bounds. We introduce the sphere bounding technique for particular codes, not average bounds. The sphere bounding estimation technique is validated by simulation results. It is also shown that sphere bounds and BP decoding performance of irregular LDPC codes are very close at bit-error-rates (BERs) $P_b$ of practical importance($10^{-5}{\leq}P_b{\leq}10^{-4}$).

Tight Bounds and Invertible Average Error Probability Expressions over Composite Fading Channels

  • Wang, Qian;Lin, Hai;Kam, Pooi-Yuen
    • Journal of Communications and Networks
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    • v.18 no.2
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    • pp.182-189
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    • 2016
  • The focus in this paper is on obtaining tight, simple algebraic-form bounds and invertible expressions for the average symbol error probability (ASEP) of M-ary phase shift keying (MPSK) in a class of composite fading channels. We employ the mixture gamma (MG) distribution to approximate the signal-to-noise ratio (SNR) distributions of fading models, which include Nakagami-m, Generalized-K ($K_G$), and Nakagami-lognormal fading as specific examples. Our approach involves using the tight upper and lower bounds that we recently derived on the Gaussian Q-function, which can easily be averaged over the general MG distribution. First, algebraic-form upper bounds are derived on the ASEP of MPSK for M > 2, based on the union upper bound on the symbol error probability (SEP) of MPSK in additive white Gaussian noise (AWGN) given by a single Gaussian Q-function. By comparison with the exact ASEP results obtained by numerical integration, we show that these upper bounds are extremely tight for all SNR values of practical interest. These bounds can be employed as accurate approximations that are invertible for high SNR. For the special case of binary phase shift keying (BPSK) (M = 2), where the exact SEP in the AWGN channel is given as one Gaussian Q-function, upper and lower bounds on the exact ASEP are obtained. The bounds can be made arbitrarily tight by adjusting the parameters in our Gaussian bounds. The average of the upper and lower bounds gives a very accurate approximation of the exact ASEP. Moreover, the arbitrarily accurate approximations for all three of the fading models we consider become invertible for reasonably high SNR.

Analysis on Upper and Lower Bounds of Stochastic LP Problems (확률적 선형계획문제의 상한과 하한한계 분석)

  • 이상진
    • Journal of the Korean Operations Research and Management Science Society
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    • v.27 no.3
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    • pp.145-156
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    • 2002
  • Business managers are often required to use LP problems to deal with uncertainty inherent in decision making due to rapid changes in today's business environments. Uncertain parameters can be easily formulated in the two-stage stochastic LP problems. However, since solution methods are complex and time-consuming, a common approach has been to use modified formulations to provide upper and lower bounds on the two-stage stochastic LP problem. One approach is to use an expected value problem, which provides upper and lower bounds. Another approach is to use “walt-and-see” problem to provide upper and lower bounds. The objective of this paper is to propose a modified approach of “wait-and-see” problem to provide an upper bound and to compare the relative error of optimal value with various upper and lower bounds. A computing experiment is implemented to show the relative error of optimal value with various upper and lower bounds and computing times.

Performance bounds of continuous-time optimal FIR filter under modeling uncertainty (모델 불확실성에 대한 연속형 최적 FIR 필터의 성능한계)

  • Yoo, Kyung-Sang;Gwon, O-Gyu
    • Journal of Institute of Control, Robotics and Systems
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    • v.1 no.1
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    • pp.20-24
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    • 1995
  • In this paper we analyze the performance bounds of the optimal FIR filter in continuous time systems with modeling uncertainty. The performance bounds are presented by the estimation error convariance and they are here expressed by the upper bounds of the difference of the estimation error covariance between the real and nominal values in case of the system with model uncertainties whose upper bounds are imperfrctly known a priori. The performance bounds of the optimal FIR filter are compared with those of the Kalman filter via a numerical example applied to the estimation of the motion of an aircraft carrier at sea, which shows the former has better performances than the latter.

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The bounds for fully saturated porous material

  • Yoon, Young-June;Jung, Jae-Yong;Chung, Jae-Pil
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.13 no.5
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    • pp.432-435
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    • 2020
  • The elasticity tensor for water may be employed to model the fully saturated porous material. Mostly water is assumed to be incompressible with a bulk modulus, however, the upper and lower bounds of off-diagonal components of the elasticity tensor of porous materials filled with water are violated when the bulk modulus is relatively high. In many cases, the generalized Hill inequality describes the general bounds of Voigt and Reuss for eigenvalues, but the bounds for the component of elasticity tensor are more realistic because the principal axis of eigenvalues of two phases, matrix and water, are not coincident. Thus in this paper, for anisotropic material containing pores filled with water, the bounds for the component of elasticity tensor are expressed by the rule of mixture and the upper and lower bounds of fully saturated porous materials are violated for low porosity and high bulk modulus of water.

Some bounds on the solution of the continuous algebraic Riccati equation

  • Moon, Young-Soo;Lee, Youngil;Kwon, Wook-Hyun
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10b
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    • pp.425-427
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    • 1993
  • Some upper bounds for the solution of the continuous algebraic Riccati equation are presented. These consist of bounds for summations of eigenvalues, products of eigenvalues, individual eigenvalues and the minimum eigenvalue of the solution matrix. Among these bounds, the first three are the first results for the upper bound of each case, while bounds for the minimum eigenvalue supplement the existing ones and require no side conditions for their validities.

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THE BEHAVIOUR OF PROBABILISTIC ERROR BOUNDS IN FLOATING POINT ALGEBRAIC PROCESSES

  • M.Mitrouli;C.Koukouvinos
    • Journal of applied mathematics & informatics
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    • v.4 no.1
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    • pp.211-222
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    • 1997
  • In this paper we present a probabilistic approach for the estimation of realistic error bounds appearing in the execution of basic algebraic floating point operations. Experimental results are carried out for the extended product the extended sum the inner product of random normalised numbers the product of random normalised ma-trices and the solution of lower triangular systems The ordinary and probabilistic bounds are calculated for all the above processes and gen-erally in all the executed examples the probabilistic bounds are much more realistic.