Results 41 to 50 of about 4,445,349 (240)
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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Probabilistic b-metric spaces and nonlinear contractions [PDF]
Fixed Point Theory and Applications, 2017 AbstractThis work is for giving the probabilistic aspect to the knownb-metric spaces (Czerwik in Atti Semin. Mat. Fis. Univ. Modena 46(2):263-276, 1998), which leads to studying the fixed point property for nonlinear contractions in this new class of spaces.
Abderrahim Mbarki, Rachid Oubrahim
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Applied General Topology, 2023 In this paper, we prove the existence of fixed point results for set-valued mappings in Menger probabilistic metric spaces equipped with an amorphous binary relation and a Hadžić -type t-norm.
Gopi Prasad +2 more
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On compactness of probabilistic metric space
Applied Mathematical Sciences, 2014 In this paper we show that every separable probabilistic metric space admits a compatible precompact probabilistic metric and that a probabilistic metric space is compact if and only if is precompact and complete. Finally we give a generalization Niemytzki-Tychonoff theorem [1] to probabilistic metric spaces.
Abderrahim Mbarki +2 more
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Dynamics and Complexity of Computrons
Entropy, 2020 We investigate chaoticity and complexity of a binary general network automata of finite size with external input which we call a computron. As a generalization of cellular automata, computrons can have non-uniform cell rules, non-regular cell ...
Murat Erkurt
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Problem Solving as Probabilistic Inference with Subgoaling: Explaining Human Successes and Pitfalls in the Tower of Hanoi. [PDF]
PLoS Computational Biology, 2016 How do humans and other animals face novel problems for which predefined solutions are not available? Human problem solving links to flexible reasoning and inference rather than to slow trial-and-error learning.
Francesco Donnarumma +2 more
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Generalized contraction mapping in probabilistic metric space
, 1970 The probabilistic metric space as one of the important generalization of metric space was introduced by K. Menger in 1942. In this paper, we briefly discuss the historical developments of contraction mappings in probabilistic metric space with some fixed
Shams-ur Rahman, K Jha
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Application of the Fisher-Rao metric to ellipse detection [PDF]
, 2007 The parameter space for the ellipses in a two dimensional image is a five dimensional manifold, where each point of the manifold corresponds to an ellipse in the image. The parameter space becomes a Riemannian manifold under a Fisher-Rao metric, which is
Stephen J. Maybank, Maybank, Stephen J.
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Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
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MB-RRT: An Inverse Kinematics Solver of Reduced Dimension
IEEE Access, 2021 The evolution of manipulator robots has increased the complexity of their models and applications, requiring that the inverse kinematics (IK) methods integrated into their control systems to have features such as fast convergence, completeness, low ...
Matheus C. Santos +5 more
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