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1000 tulosta hakusanalla Carlo Gozzi

Monte Carlo Methods for Partial Differential Equations With Applications to Electronic Design Automation

Monte Carlo Methods for Partial Differential Equations With Applications to Electronic Design Automation

Wenjian Yu; Michael Mascagni

SPRINGER VERLAG, SINGAPORE
2023
nidottu
The Monte Carlo method is one of the top 10 algorithms in the 20th century. This book is focusing on the Monte Carlo method for solving deterministic partial differential equations (PDEs), especially its application to electronic design automation (EDA) problems. Compared with the traditional method, the Monte Carlo method is more efficient when point values or linear functional of the solution are needed, and has the advantages on scalability, parallelism, and stability of accuracy. This book presents a systematic introduction to the Monte Carlo method for solving major kinds of PDEs, and the detailed explanation of relevant techniques for EDA problems especially the cutting-edge algorithms of random walk based capacitance extraction. It includes about 100 figures and 50 tables, and brings the reader a close look to the newest research results and the sophisticated algorithmic skills in Monte Carlo simulation software.
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Monte Carlo Methods In Mechanics Of Fluid And Gas

Monte Carlo Methods In Mechanics Of Fluid And Gas

Oleg Mikhailovich Belotserkovskii; Yury Iv Khlopkov

World Scientific Publishing Co Pte Ltd
2010
sidottu
This book is devoted to analysis of Monte Carlo methods developed in rarefied gas dynamics. Presented is the short history of the development of such methods, described are their main properties, their advantages and deficiencies. It is shown that the contemporary stage in the progress of computational methods cannot be regarded without a complex approach to the preparation of algorithms taking into account all the peculiarities of the problem under consideration, that is, of the physical nature of a process, the mathematical model and the theoretical aspects of computational mathematics and stochastic processes. Thoroughly investigated is the possibility of application of Monte Carlo methods in some kindred areas of science which are non-traditional for the use of statistical modeling (continuous media, turbulence). Considered are the possible directions of development of statistical modeling.
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Monte Carlo Simulation Power Analysis Using Mplus and R

Monte Carlo Simulation Power Analysis Using Mplus and R

James Peugh; Kaylee Litson

Guilford Publications
2026
nidottu
Planning effective research investigations requires sophisticated power analysis techniques. This book provides readers with clearly explained tools for using Monte Carlo simulations to estimate the needed sample sizes for adequate statistical power for a variety of modern research designs. Featuring step-by-step instructions, chapters move from simpler cross-sectional designs and path tracing rules to advanced longitudinal designs, while incorporating mediation, moderation, and missing data considerations. Worked-through applied examples with annotated Mplus and R syntax scripts, sample power analysis write-ups, and end-of-chapter suggested readings are also included. The companion website offers Mplus and R code for four additional power analysis models--latent variable moderation, discrete- and continuous-time survival analyses, cross-sectional and longitudinal two-level models, and moderated mediation--as well as supplemental computational materials.
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Monte Carlo Simulation Power Analysis Using Mplus and R

Monte Carlo Simulation Power Analysis Using Mplus and R

James Peugh; Kaylee Litson

Guilford Publications
2026
sidottu
Planning effective research investigations requires sophisticated power analysis techniques. This book provides readers with clearly explained tools for using Monte Carlo simulations to estimate the needed sample sizes for adequate statistical power for a variety of modern research designs. Featuring step-by-step instructions, chapters move from simpler cross-sectional designs and path tracing rules to advanced longitudinal designs, while incorporating mediation, moderation, and missing data considerations. Worked-through applied examples with annotated Mplus and R syntax scripts, sample power analysis write-ups, and end-of-chapter suggested readings are also included. The companion website offers Mplus and R code for four additional power analysis models--latent variable moderation, discrete- and continuous-time survival analyses, cross-sectional and longitudinal two-level models, and moderated mediation--as well as supplemental computational materials.
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Monte Carlo Methods in Biology and Medicine

Monte Carlo Methods in Biology and Medicine

Syrawood Publishing House
2025
sidottu
Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling to obtain numerical results. They are increasingly influential in biology and medicine. These methods are utilized to model complex biological systems and predict outcomes where analytical solutions are impractical. In genomics, Monte Carlo simulations help in understanding genetic variation and evolutionary processes by simulating random genetic drift and mutation effects over generations. In epidemiology, these methods are used to predict the spread of infectious diseases by modeling various scenarios of transmission and intervention strategies, aiding public health decision-making. In medical imaging, particularly in techniques like PET (Positron Emission Tomography) and SPECT (Single Photon Emission Computed Tomography), Monte Carlo simulations are used to model the transport of photons through tissues, improving image reconstruction and accuracy. This book elucidates the concepts and innovative models around prospective developments with respect to Monte Carlo methods. The topics included herein are of utmost significance and bound to provide incredible insights to readers. The readers would gain knowledge that would broaden their perspective about computer algorithms based on Monte Carlo method.
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Monte Carlo Simulation in Dependability Analysis

Monte Carlo Simulation in Dependability Analysis

Franck Bayle; Laurent Denis; Adrien Gigliati

ISTE LTD
2025
sidottu
System dependability is a complex task to grasp and analyze since it encompasses reliability, maintainability, availability, failure mode analysis and feared events. For operational safety analyses, reliability is a quantitative basis for the other disciplines of maintainability, availability and safety. Reliability metrics such as failure rate or MTBF are often misused as they are only valid for low-maintenance applications, and wrongly for others, as MTBF is only relevant for availability. In addition, in operational safety, many equations do not have explicit solutions, and Monte Carlo simulations are a little-used way of obtaining and/or confirming the solution obtained by numerical methods. Monte Carlo Simulation in Dependability Analysis fills this gap as best as we can. This task is a difficult one, since operational safety is a cross-disciplinary activity in the engineering sciences – cross-disciplinary in that it must be present throughout a product’s life cycle.
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Monte Carlo Methods in Polymer Reaction Engineering – Fundamentals, Applications and Case Studies

Monte Carlo Methods in Polymer Reaction Engineering – Fundamentals, Applications and Case Studies

JBP Soares

Wiley-VCH Verlag GmbH
2024
nidottu
This first practical approach to introduce Monte Carlo methods to those working in polymer science makes use of case studies to present a unified and comprehensive overview of various methods. The author, one of the leading experts in the field, teaches readers how to program Monte Carlo algorithms to solve their own specific problems in polymer reaction engineering, starting with simple principles and moving on to more complex examples. Additional educational software is available online. The handbook is aimed at polymer scientists and engineers in academia and industry, but is of equal interest to PhD students.
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Quattro Parole: Con un po' di logica al Nobile Signore Carlo Balbi-Valier sopra la sua risposta all'Errata-Corrige del Direttore del Monte di Pietà

Quattro Parole: Con un po' di logica al Nobile Signore Carlo Balbi-Valier sopra la sua risposta all'Errata-Corrige del Direttore del Monte di Pietà

Alessandro Carlo Fustinoni

Antigonos Verlag
2025
sidottu
Ristampa immutata dell'edizione originale del 1869. La casa editrice Antigonos specializzata nella pubblicazione di ristampe di libri storici. Ci assicuriamo che queste opere siano messe a disposizione del pubblico in buone condizioni, al fine di preservare il patrimonio culturale.
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Monte Carlo Simulation in Statistical Physics

Monte Carlo Simulation in Statistical Physics

Kurt Binder; Dieter W. Heermann

Springer-Verlag Berlin and Heidelberg GmbH Co. K
2010
sidottu
Monte Carlo Simulation in Statistical Physics deals with the computer simulation of many-body systems in condensed-matter physics and related fields of physics, chemistry and beyond, to traffic flows, stock market fluctuations, etc.). Using random numbers generated by a computer, probability distributions are calculated, allowing the estimation of the thermodynamic properties of various systems. This book describes the theoretical background to several variants of these Monte Carlo methodsand gives a systematic presentation from which newcomers can learn to perform such simulations and to analyze their results. The fifth edition covers Classical as well as Quantum Monte Carlo methods. Furthermore a new chapter on the sampling of free energy landscapes has been added. To help students in their work a special web server has been installed to host programs and discussion groups (http://wwwcp.tphys.uni-heidelberg.de). Prof. Binder was the winner of the Berni J. Alder CECAM Award for Computational Physics 2001 as well as the Boltzmann Medal in 2007.
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Monte Carlo Integration with MATLAB and Simulink

Monte Carlo Integration with MATLAB and Simulink

Arthur A. Giordano

JOHN WILEY SONS INC
2026
sidottu
Presents detailed guidance on Monte Carlo integration methods for complex applications Monte Carlo integration has become an indispensable computational tool across science, engineering, mathematics, and economics, offering effective solutions where traditional numerical integration methods fall short. Monte Carlo Integration with MATLAB and Simulink provides both a structured introduction to advanced integration techniques and a practical guide to applying them in real-world contexts. Author Arthur A. Giordano emphasizes the natural progression from deterministic traditional methods such as the use of MATLAB integral to Monte Carlo simulation-based approaches, highlighting the growing importance of random variable–driven computations in modern research and engineering applications. Covering topics from accept-rejection sampling and importance sampling to advanced algorithms such as Metropolis-Hastings, Gibbs Sampling, Slice, Hamiltonian Monte Carlo, and Sequential Monte Carlo (Particle Filtering), the book equips readers with the knowledge to handle both tractable and intractable integration problems. Extensive MATLAB examples are paired with detailed explanations, while dedicated Simulink models extend the scope of applications to robotics, control systems, neural networks, cosmology, and more. By integrating step-by-step examples, code snippets, and exploratory exercises, the book fosters an interactive learning process that encourages readers to replicate, modify, and expand on the provided material. Combining theoretical background with extensive computational demonstrations, Monte Carlo Integration with MATLAB and Simulink: Covers both deterministic and simulation-based integration methods with increasing depth and complexity Introduces advanced Monte Carlo sampling algorithms, including Slice Gibbs Sampling and Sequential Monte Carlo (Particle Filtering) Features over a dozen fully developed MATLAB examples with accompanying program code Provides detailed Simulink models for robotics, control systems, and scientific applications Includes problem sets with solutions available on a companion website Highlights the transition from classical integration to simulation methods for random processes Incorporating classical integration techniques and cutting-edge simulation methods, Monte Carlo Integration with MATLAB and Simulink is a valuable resource for advanced undergraduate and graduate students in applied mathematics, engineering, and computational sciences, as well as scientists, engineers, and researchers applying Monte Carlo integration in fields ranging from signal processing to robotics.
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Monte Carlo Methods

Monte Carlo Methods

AMERICAN MATHEMATICAL SOCIETY
2000
sidottu
Focuses on Monte Carlo methods that appear to have wide applicability and emphasizes new methods, practical applications and theoretical analysis. This book is of interest to researchers and graduate students who study and/or use Monte Carlo methods in areas of probability, statistics, theoretical physics, or computer science.
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Monte Carlo Simulations Of Disordered Systems

Monte Carlo Simulations Of Disordered Systems

Sudhir Jain

World Scientific Publishing Co Pte Ltd
1992
nidottu
This book covers the techniques of computer simulations of disordered systems. It describes how one performs Monte Carlo simulations in condensed matter physics and deals with spin-glasses, percolating networks and the random field Ising model. Other methods mentioned are molecular dynamics and Brownian dynamics. Use of flow-diagrams enables the reader to grasp both the problem and its solution more readily. The book deals with highly complicated problems at a relatively simple level and will be most useful for advanced undergraduate and other courses in computational modelling.
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