Results 31 to 40 of about 18,707 (285)
Nonlinear Analysis, 2019 In this paper, we introduce the concept of enhanced probabilistic metric space (briefly EPM-space) as a type of probabilistic metric space. Also, we investigate the existence of fixed points for a (finite or infinite) linear combination of different ...
Jafari Jafari +3 more
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Building Energy Consumption Prediction Using a Deep-Forest-Based DQN Method
Buildings, 2022 When deep reinforcement learning (DRL) methods are applied in energy consumption prediction, performance is usually improved at the cost of the increasing computation time.
Qiming Fu +5 more
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An Improved Iterative Reweighted STAP Algorithm for Airborne Radar
Remote Sensing, 2022 In recent years, sparse recovery-based space-time adaptive processing (SR-STAP) technique has exhibited excellent performance with insufficient samples.
Weichen Cui +3 more
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International Journal of Interactive Multimedia and Artificial Intelligence, 2022 Sampling-based motion planning in the field of robot motion planning has provided an effective approach to finding path for even high dimensional configuration space and with the motivation from the concepts of sampling based-motion planners, this paper
Lhilo Kenye, Rahul Kala
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Turbo receivers for interleave-division multiple-access systems [PDF]
, 2009 In this paper several turbo receivers for Interleave-Division Multiple-Access (IDMA) systems will be discussed. The multiple access system model is presented first. The optimal, Maximum A Posteriori (MAP) algorithm, is then presented.
Cristea, Bogdan Eugen +3 more
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$I^K_ν$-Convergence of functions in probabilistic normed spaces
, 2023 In this paper we study $I^K$-convergence of functions with respect to probabilistic norm $ν$ which is a generalization of $I^*_ν$-convergence in probabilistic norm spaces. We also study on $I^K$-Cauchy functions and $I^K$-limit points with respect to probabilistic norm $ν$ in the same space.
Banerjee, Amar Kumar, Paul, Mahendranath
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Some Results on Best Proximity Points of Cyclic Contractions in Probabilistic Metric Spaces
Journal of Function Spaces, 2015 This paper investigates properties of convergence of distances of p-cyclic contractions on the union of the p subsets of an abstract set X defining probabilistic metric spaces and Menger probabilistic metric spaces as well as the characterization of ...
Manuel De la Sen, Erdal Karapınar
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Strong and weak convergences in 2-probabilistic normed spaces
Advances in the Theory of Nonlinear Analysis and its Application, 2021 In this paper, we have introduced the notions of strong and weak convergences in 2-probabilistic normed spaces (2-PN spaces) and established some of its properties. Later, we have defined the strong and weak boundedness of a linear map between two 2-PN spaces and proved a necessary and sufficient condition for the linear map between two 2-PN spaces to ...
Harikrishnan PANACKAL +3 more
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A quantitative probabilistic investigation into the accumulation of rounding errors in numerical ODE solution. [PDF]
, 2009 We examine numerical rounding errors of some deterministic solvers for systems of ordinary differential equations (ODEs) from a probabilistic viewpoint. We show that the accumulation of rounding errors results in a solution which is inherently random and
Turner, Amanda G. +2 more
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Solution Representation Learning in Multi-Objective Transfer Evolutionary Optimization
IEEE Access, 2021 This paper presents a first study on solution representation learning for inducing greater alignment and hence positive transfers between distinct multi-objective optimization tasks that bear discrepancies in their original search spaces.
Ray Lim +4 more
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