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New Uniform Parametric Error Bounds
Journal of Optimization Theory and Applications, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Upper Error Bound Selection in Bounded Parameter Estimation
IFAC Proceedings Volumes, 1994Abstract The problem of upper error bound selection in bounded parameter estimation for models linear-in-the-parameters is considered. It is shown that this selection implies a trade-off between posterior parametric and nonparametric uncertainty. A minimum uncertainty description of the model behaviour is obtained from min-max parameter estimation ...
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2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019
We present a feedback motion planning algorithm, Bounded-Error LQR-Trees, that leverages reinforcement learning theory to find a policy with a bounded amount of error. The algorithm composes locally valid linear-quadratic regulators (LQR) into a nonlinear controller, similar to how LQR-Trees constructs its policy, but minimizes the cost of the ...
Barrett Ames, George Konidaris
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We present a feedback motion planning algorithm, Bounded-Error LQR-Trees, that leverages reinforcement learning theory to find a policy with a bounded amount of error. The algorithm composes locally valid linear-quadratic regulators (LQR) into a nonlinear controller, similar to how LQR-Trees constructs its policy, but minimizes the cost of the ...
Barrett Ames, George Konidaris
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Computing in Science & Engineering, 2021
Prompted by previous work published in this magazine, in this article we focus on the derivation of global analytical bounds for the error function of a real argument. Using an integral representation of this function, we obtain two simple and accurate lower bounds, which complement a well-known upper bound given long ago by Polya.
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Prompted by previous work published in this magazine, in this article we focus on the derivation of global analytical bounds for the error function of a real argument. Using an integral representation of this function, we obtain two simple and accurate lower bounds, which complement a well-known upper bound given long ago by Polya.
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Bounds and error bounds for queueing networks
Annals of Operations Research, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Bounded‐error estimation using dead zone and bounding ellipsoid
International Journal of Adaptive Control and Signal Processing, 1994AbstractThe use of a dead zone and a bounding ellipsoid for parameter estimation when measurement errors are bounded is discussed. the size of the dead zone is set to be exactly equal to the assumed noise bound. The algorithm retains the properties of computing parameter point estimates and allows a bounding ellipsoid to be computed at each iterative ...
Evans, R. J., Zhang, C., Soh, Y. C.
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Naval Research Logistics, 1988
We explore the properties of the discounted total cost function for the economic order quantity. We show that it is convex. Furthermore, it is shown that the classical economic order quantity (based on Wilson's formula) is not less than the true optimum value based on discounting.
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We explore the properties of the discounted total cost function for the economic order quantity. We show that it is convex. Furthermore, it is shown that the classical economic order quantity (based on Wilson's formula) is not less than the true optimum value based on discounting.
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On Error Bounds for Quasinormal Programs
Journal of Optimization Theory and Applications, 2010Let \(I\) and \(I_{0}\) be finite index sets, \(h_{i}:\mathbb{R}^{m}\rightarrow \mathbb{R}\) \((i\in I\cup I_{0})\) be continuously differentiable functions, and \(C:=\{y\in \mathbb{R}^{m}:h_{i}(y)\leq 0\) \((i\in I),\) \(h_{i}(y)=0\) \((i\in I_{0})\}\). The main result states that, assuming that the gradients \(\nabla h_{i}(y)\) \((i\in I\cup I_{0})\)
Minchenko, L., Tarakanov, A.
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2016
In this chapter, we show that our preceding analysis can be applied to estimation problems as well. The results can be viewed as implications of the performance bounds on power gain and in variance minimization presented in the previous two chapters. In particular, we derive fundamental estimation bounds for estimation systems that are not necessarily ...
Song Fang, Jie Chen, Hideaki Ishii
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In this chapter, we show that our preceding analysis can be applied to estimation problems as well. The results can be viewed as implications of the performance bounds on power gain and in variance minimization presented in the previous two chapters. In particular, we derive fundamental estimation bounds for estimation systems that are not necessarily ...
Song Fang, Jie Chen, Hideaki Ishii
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Threshold Detection Error Bounds
IETE Journal of Research, 1984The computation of error probability in data transmission, mobile telephony, SSMA requires use of bounds on the probability of sum of random variables. This paper reviews some useful bounds not well known to electrical engineers. Bounds of both the polynomial and the exponential type have been discussed.
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