Random Motions in Markov and Semi-Markov Random Environments 2. Anatoliy Swishchuk

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       Series Editor

       Nikolaos Limnios

      Random Motions in Markov and Semi-Markov Random Environments 2

       High-dimensional Random Motions and Financial Applications

      Anatoliy Pogorui

      Anatoliy Swishchuk

      Ramón M. Rodríguez-Dagnino

      First published 2021 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.

      Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:

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      John Wiley & Sons, Inc.

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      © ISTE Ltd 2021

      The rights of Anatoliy Pogorui, Anatoliy Swishchuk and Ramón M. Rodríguez-Dagnino to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.

      Library of Congress Control Number: 2020946634

      British Library Cataloguing-in-Publication Data

      A CIP record for this book is available from the British Library

      ISBN 978-1-78630-706-4

      Preface

      Motion is an essential element in our daily life. Thoughts related to motion can be found in the ancient Greek philosophers; however, we have to look several centuries ahead for relevant mathematical models. Galileo Galilei, Isaac Newton and Johannes Kepler, between the years 1550–1650, made remarkable advances in the construction of mathematical models for deterministic motion. Further advances in this line were made by Leonhard Euler and William Rowan Hamilton, and, in 1778, Joseph-Louis Lagrange proposed a new formulation of classical mechanics. This new formulation is based on the optimization of energy functionals, СКАЧАТЬ