A Mean Field Approximation for the CML Model
On the Approximation Error of Mean-Field Models
... Then the macroscopic behaviors of the stochastic system can be approximated using the mean-field model, e.g., the stationary distribution of the stochastic system may be ap- Permission to make ...
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Applying Mean-field Approximation to Continuous Time Markov Chains
... The mean-field analysis technique is used to perform anal- ysis of a systems with a large number of components to determine the emergent deterministic behaviour and how this behaviour modifies when its ...
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Applying Mean-Field Approximation to Continuous Time Markov Chains
... the model and later for model ...the mean- field analysis of the model and the age distributions calculated by considering the contact ...the model parameters are calculated ...
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Failure of mean-field approximation in weakly coupled dilaton gravity
... Therefore, we still need simple solvable models to address the black hole information puzzle. One may hope to resolve it in the simplified context of two-dimensional dilaton gravity. This class of models has been ...
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Mean Field Variational Approximation for Continuous-Time Bayesian Networks
... related model. Their model is similar to an HMM, in which the hidden chain is a continuous-time Markov process and there are (noisy) observations at discrete points along the ...
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Ferrimagnetism in the Mean-field Approximation of a Mixed Spin Ising Nanowire System
... the mean-field approximation (MFA), in order to clarify the physical background for the characteristic phenomena observed in the ferrimagnetic mixed nanowire ...the mean-field theory ...
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On a Boltzmann mean field model for knowledge growth
... In this paper we investigate the existence and uniqueness of solutions to a Boltz- mann mean field game (BMFG) model for knowledge growth, with a particular focus on the construction of the so-called ...
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Estimation of Software Reliability by Sequential Testing with Simulated Annealing of Mean Field Approximation
... of mean field approximation for finding the possible minimum number of failed components in the sequential ...the mean field approximation is also ...
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Crowd-Averse Robust Mean-Field Games: Approximation via State Space Extension
... robust mean-field games: approximation via state space extension ...coupling mean-field term measuring the congestion resulting from the collective behavior, which motivates the term ...
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Crowd-averse robust mean-field games: approximation via state space extension
... robust mean-field games: approximation via state space extension ...coupling mean-field term measuring the congestion resulting from the collective behavior, which motivates the term ...
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Nonequivalent Ensembles for the Mean Field φ6 Spin Model
... the mean field 𝜑𝜑 6 spin model in the framework of the micro-canonical ensemble as a function of the energy and ...spin model. The interesting point we found is that like φ 4 model the ...
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Spectral Gap in Mean-Field O(n)-Model
... 6. The Critical Regime, Proof of Theo. 3 We conclude our analysis by investigating the critical case β = n and prove Theorem 3. As before, we distinguish between n = 1 and multi-component systems n ≥ 2: 6.1. Critical ...
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A mean field model for movement induced changes in the beta rhythm
... mass model would be ideal for this scale, if the question of interest related to rate rather than spike, which suggests instead a simulation of a spiking neural network ...a mean field reduction for ...
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Mean field games: A toy model on an Erdös-Renyi graph.
... of mean field games cannot be systematically constructed by a contraction ...a mean field game thus requires another method; for instance, it may be based on a fixed point theorem without ...
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Conditional mean field
... original model, then incrementally reintroduce ...glass model [16]. Ernst Ising developed his model in order to explain the phenomenon of “spontaneous magnetization” in ...Ising model, but ...
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The Euler–Maruyama approximation for the asset price in the mean-reverting-theta stochastic volatility model
... above models which assume θ < 1 (or β < 1) are rejected and those which assume θ ≥ 1 (or β ≥ 1) are not rejected. For example, applying the Generalized Method Moment, Chan et al. [11] give θ = 1 . 449. Using the ...
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Spatiotemporal multi-resolution approximation of the Amari type neural field model
... dynamic model. Neural mass and neural field models are ideal candidates for estimation algorithms due to their strong links with physiology and their ...neural field models represent a cortical ...
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Requirements model of collaborative mobile learning (CML)
... The model should provide rich amount of information through M- learning for collaborative learning ...instructional model for Android mobile application combining the CL and M-learning concepts calls ...
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Mean-Field Model of Immobilized Enzymes Embedded in a Grafted Polymer Layer
... our model of a protein that may adopt a globular denatured state is that we predict a critical distance beyond which penetration of a protein into the grafted polymer layer will result in ...our model, ...
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Heterogenous mean-field analysis of a generalized voter-like model on networks
... heterogeneous mean-field (HMF) level that (i) yields a unified picture for existing copy/invasion processes and (ii) allows for the introduction of further heterogeneity through degree-selectivity ...HMF ...
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