Numerical simulations in physics often require estimating a multitude of parameters, making the process computationally ...
Abstract: When solving certain partial differential equations, namely those describing transient behaviour of linear dynamical systems, Laplace transforms in two variables can very be useful. However, ...
Abstract: The problem of distributed parameter estimation from binary quantized observations is studied when the unquantized observations are corrupted by combined multiplicative and additive Gaussian ...
Parameter Estimation of DAB Converter Using Intelligent Algorithms and Steady-State Modeling Considering Nonidealities (IEEE Transactions on Industrial Electronics (*IEEE TIE*)) Codes for parameter ...
OpenAI recently unveiled its latest artificial intelligence (AI) models, o1-preview and o1-mini (also referred to as “Strawberry”), claiming a significant leap in the reasoning capabilities of large ...
Smart Computational Imaging (SCI) Laboratory, Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210094, China Smart Computational Imaging Research Institute (SCIRI) of Nanjing ...
% This code fits a SIR model for LA county data on COVID-19 - https://github.com/datadesk/california-coronavirus-data and http://publichealth.lacounty.gov/media ...
ABSTRACT: This paper studied the clustering analysis of panel data, the specification test of panel data model and its parameter estimation. By carrying out clustering analysis on panel data, we ...
A new tool to break down and segment large data set problems and problems with many parameters in particle physics could have a wide range of applications. One of the major challenges in particle ...
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