Results 11 to 20 of about 7,844,010 (281)

Mixed H2/H∞ filtering for uncertain systems with regional pole assignment [PDF]

open access: yes, 2005
Copyright [2005] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services.
Wang, Z, Shu, H, Hung, Y, Yang, F
core   +7 more sources

Robust filtering for bilinear uncertain stochastic discrete-time systems [PDF]

open access: yes, 2002
Copyright [2002] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services.
Qiao, H, Wang, Z
core   +6 more sources

Optimal Control with Partially Observed Regime Switching: Discounted and Average Payoffs

open access: yesMathematics, 2022
We consider an optimal control problem with the discounted and average payoff. The reward rate (or cost rate) can be unbounded from above and below, and a Markovian switching stochastic differential equation gives the state variable dynamic.
Beatris Adriana Escobedo-Trujillo   +3 more
doaj   +1 more source

Optimal Real-Time Filters for Linear Prediction Problems [PDF]

open access: yesJournal of Time Series Econometrics, 2016
Abstract The classic model-based paradigm in time series analysis is rooted in the Wold decomposition of the data-generating process into an uncorrelated white noise process. By design, this universal decomposition is indifferent to particular features of a specific prediction problem (e.
Wildi, Marc, McElroy, Tucker
openaire   +1 more source

Efficient 0/1-Multiple-Knapsack Problem Solving by Hybrid DP Transformation and Robust Unbiased Filtering

open access: yesAlgorithms, 2022
The multiple knapsack problem (0/1-mKP) is a valuable NP-hard problem involved in many science-and-engineering applications. In current research, there exist two main approaches: 1.
Patcharin Buayen, Jeeraporn Werapun
doaj   +1 more source

Robust filtering for a class of stochastic uncertain nonlinear time-delay systems via exponential state estimation [PDF]

open access: yes, 2001
Copyright [2001] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services.
Wang, Z, Burnham, KJ
core   +6 more sources

Variance-constrained filtering for nonlinear systems with randomly occurring quantized measurements: recursive scheme and boundedness analysis

open access: yesAdvances in Difference Equations, 2019
In this paper, the robust optimal filtering problem is discussed for time-varying networked systems with randomly occurring quantized measurements via the variance-constrained method. The stochastic nonlinearity is considered by statistical form.
Chaoqing Jia, Jun Hu
doaj   +1 more source

A Sliding Window Optimal Tracking Differentiator Filtering Method for Satellite Telemetry Data

open access: yesXibei Gongye Daxue Xuebao, 2020
The initial satellite telemetry data acquired by ground stations usually contain noise and outlier interference. In order to ensure the accurate analysis of satellite status, the telemetry data need to be filtered. In this paper, a sliding window optimal

doaj   +1 more source

Comparative Study of Markov Chain Filtering Schemas for Stabilization of Stochastic Systems under Incomplete Information

open access: yesMathematics, 2022
The object under investigation is a controllable linear stochastic differential system affected by some external statistically uncertain piecewise continuous disturbances.
Alexey Bosov, Andrey Borisov
doaj   +1 more source

Implicit Filtering and Optimal Design Problems [PDF]

open access: yes, 1995
Implicit filtering is a form of the gradient projection method of Bertsekas in which the stepsize in a difference approximation of the gradient is changed as the iteration progresses. In this way the algorithm is able to avoid certain types of local minima and in some cases find accurate approximations to the global minimum.
P. Gilmore   +3 more
openaire   +1 more source

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