03811nam a22003974u 4500 10.1002/9781119989271 Wiley 20251030120321.0 cr nn 008mam|a 231122t2023||||xxu fs| |0|| 0|eng|| 9781119989271 electronic 10.1002/9781119989271 doi eng Poljak, Dragan aut 92300 Deterministic and Stochastic Modeling in Computational Electromagnetics Integral and Differential Equation Approaches [electronic resource] Dragan Poljak, Anna Šušnjara 1 Wiley 2023 Wiley 2023 576pp.; text txt rdacontent computer c rdamedia online resource cr rdacarrier text file rdaft PDF Deterministic and Stochastic Modeling in Computational Electromagnetics Help protect your network with this important reference work on cyber security Deterministic computational models are those for which all inputs are precisely known, whereas stochastic modeling reflects uncertainty or randomness in one or more of the data inputs. Many problems in computational engineering therefore require both deterministic and stochastic modeling to be used in parallel, allowing for different degrees of confidence and incorporating datasets of different kinds. In particular, non-intrusive stochastic methods can be easily combined with widely used deterministic approaches, enabling this more robust form of data analysis to be applied to a range of computational challenges. Deterministic and Stochastic Modeling in Computational Electromagnetics provides a rare treatment of parallel deterministic-stochastic computational modeling and its beneficial applications. Unlike other works of its kind, which generally treat deterministic and stochastic modeling in isolation from one another, it aims to demonstrate the usefulness of a combined approach and present particular use-cases in which such an approach is clearly required. It offers a non-intrusive stochastic approach which can be incorporated with minimal effort into virtually all existing computational models. Readers will also find: A range of specific examples demonstrating the efficiency of deterministic-stochastic modeling Computational examples of successful applications including ground penetrating radars (GPR), radiation from 5G systems, transcranial magnetic and electric stimulation (TMS and TES), and more Introduction to fundamental principles in field theory to ground the discussion of computational modeling Deterministic and Stochastic Modeling in Computational Electromagnetics is a valuable reference for researchers, including graduate and undergraduate students, in computational electromagnetics, as well as to multidisciplinary researchers, engineers, physicists, and mathematicians. Electromagnetic Theory 91431 Computational / Numerical Methods RF / Microwave Theory & Techniques 91221 Computational modeling computer engineering; CEM; data analysis; data modeling; electrical engineering; ground penetrating radars; GPR; grounding systems; 5G system; transcranial magnetic simulation; TMS; transcranial electrical simulation; ILS Šušnjara, Anna aut 92301 Printed edition: 9781119989240 https://doi.org/10.1002/9781119989271 Wiley Online Library https://onlinelibrary.wiley.com/action/showBook?doi=10.1002%2F9781119989271 Wiley Online Library Cover Image https://onlinelibrary.wiley.com/cms/asset/1f2d50c5-07f5-4d45-98d0-398b22388dea/9781119989271.cover.gif Wiley Online Library 67296 67296