Results 41 to 50 of about 3,035,814 (240)
This paper proposes a new spatiotemporal chaos model, which is a logistic-dynamic coupled logistic map lattice (LDCML). Through a large number of simulation experiments and theoretical analysis, it can be proved that a chaotic region has the larger ...
Wang Xingyuan +4 more
doaj +1 more source
Scanning the Parameter Space of Holographic Superconductors
We study various physical quantities associated with holographic s-wave superconductors as functions of the scaling dimensions of the dual condensates. A bulk scalar field with negative mass squared $m^2$, satisfying the Breitenlohner-Freedman stability ...
A. Yarom +20 more
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Hough Transform Implementation For Event-Based Systems: Concepts and Challenges
Hough transform (HT) is one of the most well-known techniques in computer vision that has been the basis of many practical image processing algorithms. HT however is designed to work for frame-based systems such as conventional digital cameras. Recently,
Sajjad Seifozzakerini +4 more
doaj +1 more source
Expanding the parameter space of natural supersymmetry
SUSY/SUGRA models with naturalness defined via small μ are constrained due to experiment on the relic density and the experimental limits on the WIMP-proton cross-section and WIMP annihilation cross-section from indirect detection experiments ...
Amin Aboubrahim, Wan-Zhe Feng, Pran Nath
doaj +1 more source
Parton Distributions in the Impact Parameter Space
Parton distributions in impact parameter space, which are obtained by Fourier transforming GPDs, exhibit a significant deviation from axial symmetry when the target and/or quark is transversely polarized. In combination with the final state interactions,
Donal B. Day +6 more
core +2 more sources
Storm Waves at the Shoreline: When and Where Are Infragravity Waves Important?
Infragravity waves (frequency, f = 0.005–0.05 Hz) are known to dominate hydrodynamic and sediment transport processes close to the shoreline on low-sloping sandy beaches, especially when incident waves are large.
Oliver Billson +2 more
doaj +1 more source
Empirical likelihood on the full parameter space
We extend the empirical likelihood of Owen [Ann. Statist. 18 (1990) 90-120] by partitioning its domain into the collection of its contours and mapping the contours through a continuous sequence of similarity transformations onto the full parameter space.
Tsao, Min, Wu, Fan
core +1 more source
Systematic Parameter Space Search of Extended Quark-Lepton Complementarity [PDF]
We systematically investigate the parameter space of neutrino and charged lepton mass matrices for textures motivated by an extended quark-lepton complementarity.
Ahluwalia +91 more
core +5 more sources
Inference in High-Dimensional Parameter Space [PDF]
Model parameter inference has become increasingly popular in recent years in the field of computational epidemiology, especially for models with a large number of parameters. Techniques such as Approximate Bayesian Computation (ABC) or maximum/partial likelihoods are commonly used to infer parameters in phenomenological models that best describe some ...
openaire +3 more sources
Parameter Identifiability for Nonlinear LPV Models
Linear parameter varying (LPV) models are being increasingly used as a bridge between linear and nonlinear models. From a mathematical point of view, a large class of nonlinear models can be rewritten in LPV or quasi-LPV forms easing their analysis. From
Srinivasarengan Krishnan +3 more
doaj +1 more source

