Bücher von Santanu Saha Ray

This book is a compendium of the proceedings of the International Conference on Applied Analysis, Computation, and Mathematical Modelling in Engineering (AACMME-2021). The book covers a variety of applications such as mechanical, acoustical, physical, electrical, bio-mathematical, and computational fluid dynamics. Since mathematical modeling necessitates a wide range of skills and methods, the book concentrates on techniques that will be of specific interest to engineers, scientists, and those who work with discrete and continuous systems models. This book guides students, researchers, and professionals through the new approaches, the powerful tools for quickly mastering the most popular mathematical and computational models used in engineering and science. These new approaches enable readers to not only systematically create effective models, but also extend these models to any macroscopic physical structure.

The modelling of systems by differential equations usually requires that the parameters involved be completely known. Such models often originate from problems in physics or economics where we have insufficient information on parameter values. One important class of stochastic mathematical models is stochastic partial differential equations (SPDEs), which can be seen as deterministic partial differential equations (PDEs) with finite or infinite dimensional stochastic processes - either with colour noise or white noise. Though white noise is a purely mathematical construction, it can be a good model for rapid random fluctuations.Stochastic Integral and Differential Equations in Mathematical Modelling concerns the analysis of discrete-time approximations for stochastic differential equations (SDEs) driven by Wiener processes. It also provides a theoretical basis for working with SDEs and stochastic processes.This book is written in a simple and clear mathematical logical language, with basic definitions and theorems on stochastic calculus provided from the outset. Each chapter contains illustrated examples via figures and tables. The reader can also construct new wavelets by using the procedure presented in the book. Stochastic Integral and Differential Equations in Mathematical Modelling fulfils the existing gap in the literature for a comprehensive account of this subject area.

With elegantly defined examples and rigorously explained theorem proofs, this book presents concepts in the theory of graphs and algorithms, and their applications. It describes many key algorithms and uses simple, clear, and logical mathematical language.