Monte Carlo simulation is one of the best tools for performing realistic analysis of complex systems as it allows most of the limiting assumptions on system behavior to be relaxed.
This book provides an introduction to the mathematical modelling of real world financial markets and the rational pricing of derivatives, which is part of the theory that not only underpins modern financial practice but is a thriving area of mathematical research.
Iterative Methods for Queuing and Manufacturing Systems introduces the recent advances and developments in iterative methods for solving Markovian queuing and manufacturing problems.
Learning and Generalization provides a formal mathematical theory addressing intuitive questions of the type: How does a machine learn a concept on the basis of examples?
Written by Nick Bingham, Chairman and Professor of Statistics at Birkbeck College, and Rudiger Kiesel, an "e;up-and-coming"e; academic, Risk Neutrality will benefit the Springer Finance Series in many ways.
Uncertainty is an inherent feature of both properties of physical systems and the inputs to these systems that needs to be quantified for cost effective and reliable designs.
Recent Advances in System Reliability discusses developments in modern reliability theory such as signatures, multi-state systems and statistical inference.
Randomized Algorithms discusses two problems of fine pedigree: counting and generation, both of which are of fundamental importance to discrete mathematics and probability.
Measure, Integral and Probability is a gentle introduction that makes measure and integration theory accessible to the average third-year undergraduate student.
Over the past decades, although stochastic system control has been studied intensively within the field of control engineering, all the modelling and control strategies developed so far have concentrated on the performance of one or two output properties of the system.
Developed from a set of lecture notes by Professor Kamen and since developed and refined by both authors, this introductory yet comprehensive study is a prime example in its field.
Discrete-time Stochastic Systems gives a comprehensive introduction to the estimation and control of dynamic stochastic systems and provides complete derivations of key results such as the basic relations for Wiener filtering.
The Volume 1 book on Accelerating Discoveries in Data Science and Artificial Intelligence (Proceedings of ICDSAI 2023), that was held on April 24-25, 2023 by CSUSB USA, the International Association of Academicians (IAASSE), and the Lendi Institute of Engineering and Technology, Vizianagaram, India is intended to be used as a reference book for researchers and practitioners in the disciplines of AI and data science.
This book introduces readers to the financial markets, derivatives, structured products and how the products are modelled and implemented by practitioners.
Limit theorems for stochastic processes are an important part of probability theory and mathematical statistics and one model that has attracted the attention of many researchers working in the area is that of limit theorems for randomly stopped stochastic processes.
Reliability theory is of fundamental importance for engineers and managers involved in the manufacture of high-quality products and the design of reliable systems.
Methods of global analysis and stochastic analysis are most often applied in mathematical physics as separate entities, thus forming important directions in the field.
Hereditary systems (or systems with either delay or after-effects) are widely used to model processes in physics, mechanics, control, economics and biology.
Reliability and Safety of Complex Technical Systems and Processes offers a comprehensive approach to the analysis, identification, evaluation, prediction and optimization of complex technical systems operation, reliability and safety.
This textbook provides a comprehensive exploration of anomalous stochastic processes and extreme events, commonly referred to as "e;black swans,"e; with a particular focus on (multi-)fractal approaches and continuous-time random walks.
The main challenge in the study of nonautonomous phenomena is to understand the very complicated dynamical behaviour both as a scientific and mathematical problem.
This 2nd edition of the book focuses on the properties of stationary states in chaotic systems of particles or fluids, setting aside the theory of how these states are achieved.
The Volume 1 book on Accelerating Discoveries in Data Science and Artificial Intelligence (Proceedings of ICDSAI 2023), that was held on April 24-25, 2023 by CSUSB USA, the International Association of Academicians (IAASSE), and the Lendi Institute of Engineering and Technology, Vizianagaram, India is intended to be used as a reference book for researchers and practitioners in the disciplines of AI and data science.
This book concentrates on the famous Grothendieck inequality and the continued search for the still unknown best possible value of the real and complex Grothendieck constant (an open problem since 1953).
In this book, the optimal transportation problem (OT) is described as a variational problem for absolutely continuous stochastic processes with fixed initial and terminal distributions.
This book offers a novel multi-portfolio approach and stochastic programming formulations for modeling and solving contemporary supply chain risk management problems.
This book organizes and explains, in a systematic and pedagogically effective manner, recent advances in path integral solution techniques with applications in stochastic engineering dynamics.
Dynamics of Democratic Elections explores modeling approaches to democratic elections and opinion dynamics at the intersection of mathematics, political science, and computational modeling.
Dynamics of Democratic Elections explores modeling approaches to democratic elections and opinion dynamics at the intersection of mathematics, political science, and computational modeling.
This book investigates the relationship between empirical reality and theoretical modelling in Earth sciences, focusing on how empirical experiments and theoretical models interact.
