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Books > Science & Mathematics > Mathematics > Applied mathematics > Stochastics

Best Books gegradeerde leesreeks: Vlak 1 Boek 2: Gr 2: Leesboek - Huistaal (Afrikaans, Paperback): Best Books Paneel Best Books gegradeerde leesreeks: Vlak 1 Boek 2: Gr 2: Leesboek - Huistaal (Afrikaans, Paperback)
Best Books Paneel
R70 R61 Discovery Miles 610 Save R9 (13%) Shipped within 14 - 18 working days
Introduction to Malliavin Calculus (Paperback): David Nualart, Eulalia Nualart Introduction to Malliavin Calculus (Paperback)
David Nualart, Eulalia Nualart
R753 R646 Discovery Miles 6 460 Save R107 (14%) Shipped within 20 - 25 working days

This textbook offers a compact introductory course on Malliavin calculus, an active and powerful area of research. It covers recent applications, including density formulas, regularity of probability laws, central and non-central limit theorems for Gaussian functionals, convergence of densities and non-central limit theorems for the local time of Brownian motion. The book also includes a self-contained presentation of Brownian motion and stochastic calculus, as well as Levy processes and stochastic calculus for jump processes. Accessible to non-experts, the book can be used by graduate students and researchers to develop their mastery of the core techniques necessary for further study.

Stochastic Analysis of Scaling Time Series - From Turbulence Theory to Applications (Hardcover): Francois G. Schmitt, Yongxiang... Stochastic Analysis of Scaling Time Series - From Turbulence Theory to Applications (Hardcover)
Francois G. Schmitt, Yongxiang Huang
R1,234 R1,170 Discovery Miles 11 700 Save R64 (5%) Shipped within 20 - 25 working days

Multi-scale systems, involving complex interacting processes that occur over a range of temporal and spatial scales, are present in a broad range of disciplines. Several methodologies exist to retrieve this multi-scale information from a given time series; however, each method has its own limitations. This book presents the mathematical theory behind the stochastic analysis of scaling time series, including a general historical introduction to the problem of intermittency in turbulence, as well as how to implement this analysis for a range of different applications. Covering a variety of statistical methods, such as Fourier analysis and wavelet transforms, it provides readers with a thorough understanding of the techniques and when to apply them. New techniques to analyse stochastic processes, including empirical mode decomposition, are also explored. Case studies, in turbulence and ocean sciences, are used to demonstrate how these statistical methods can be applied in practice, for students and researchers.

Random Graphs and Complex Networks: Volume 1 (Hardcover): Remco van der Hofstad Random Graphs and Complex Networks: Volume 1 (Hardcover)
Remco van der Hofstad
R1,033 Discovery Miles 10 330 Shipped within 20 - 25 working days

This rigorous introduction to network science presents random graphs as models for real-world networks. Such networks have distinctive empirical properties and a wealth of new models have emerged to capture them. Classroom tested for over ten years, this text places recent advances in a unified framework to enable systematic study. Designed for a master's-level course, where students may only have a basic background in probability, the text covers such important preliminaries as convergence of random variables, probabilistic bounds, coupling, martingales, and branching processes. Building on this base - and motivated by many examples of real-world networks, including the Internet, collaboration networks, and the World Wide Web - it focuses on several important models for complex networks and investigates key properties, such as the connectivity of nodes. Numerous exercises allow students to develop intuition and experience in working with the models.

Stochastic Dynamics, Filtering and Optimization (Hardcover): Debasish Roy, G. Visweswara Rao Stochastic Dynamics, Filtering and Optimization (Hardcover)
Debasish Roy, G. Visweswara Rao
R1,899 R1,784 Discovery Miles 17 840 Save R115 (6%) Shipped within 20 - 25 working days

Targeted at graduate students, researchers and practitioners in the field of science and engineering, this book gives a self-contained introduction to a measure-theoretic framework in laying out the definitions and basic concepts of random variables and stochastic diffusion processes. It then continues to weave into a framework of several practical tools and applications involving stochastic dynamical systems. These include tools for the numerical integration of such dynamical systems, nonlinear stochastic filtering and generalized Bayesian update theories for solving inverse problems and a new stochastic search technique for treating a broad class of non-convex optimization problems. MATLAB (R) codes for all the applications are uploaded on the companion website.

The Probability Companion for Engineering and Computer Science (Paperback): Adam Prugel-Bennett The Probability Companion for Engineering and Computer Science (Paperback)
Adam Prugel-Bennett
R1,007 Discovery Miles 10 070 Shipped within 20 - 25 working days

This friendly guide is the companion you need to convert pure mathematics into understanding and facility with a host of probabilistic tools. The book provides a high-level view of probability and its most powerful applications. It begins with the basic rules of probability and quickly progresses to some of the most sophisticated modern techniques in use, including Kalman filters, Monte Carlo techniques, machine learning methods, Bayesian inference and stochastic processes. It draws on thirty years of experience in applying probabilistic methods to problems in computational science and engineering, and numerous practical examples illustrate where these techniques are used in the real world. Topics of discussion range from carbon dating to Wasserstein GANs, one of the most recent developments in Deep Learning. The underlying mathematics is presented in full, but clarity takes priority over complete rigour, making this text a starting reference source for researchers and a readable overview for students.

Introduction to Malliavin Calculus (Hardcover): David Nualart, Eulalia Nualart Introduction to Malliavin Calculus (Hardcover)
David Nualart, Eulalia Nualart
R1,869 R1,753 Discovery Miles 17 530 Save R116 (6%) Shipped within 20 - 25 working days

This textbook offers a compact introductory course on Malliavin calculus, an active and powerful area of research. It covers recent applications, including density formulas, regularity of probability laws, central and non-central limit theorems for Gaussian functionals, convergence of densities and non-central limit theorems for the local time of Brownian motion. The book also includes a self-contained presentation of Brownian motion and stochastic calculus, as well as Levy processes and stochastic calculus for jump processes. Accessible to non-experts, the book can be used by graduate students and researchers to develop their mastery of the core techniques necessary for further study.

Computational Uncertainty Quantification for Inverse Problems (Paperback): Johnathan M. Bardsley Computational Uncertainty Quantification for Inverse Problems (Paperback)
Johnathan M. Bardsley
R1,357 Discovery Miles 13 570 Shipped within 20 - 25 working days

This book is an introduction to both computational inverse problems and uncertainty quantification (UQ) for inverse problems. The book also presents more advanced material on Bayesian methods and UQ, including Markov chain Monte Carlo sampling methods for UQ in inverse problems. Each chapter contains MATLAB (R) code that implements the algorithms and generates the figures, as well as a large number of exercises accessible to both graduate students and researchers. Computational Uncertainty Quantification for Inverse Problems is intended for graduate students, researchers, and applied scientists. It is appropriate for courses on computational inverse problems, Bayesian methods for inverse problems, and UQ methods for inverse problems.

Handbook on Loss Reserving 2016 (Paperback, 2016 ed.): Michael Radtke, Klaus D. Schmidt, Anja Schnaus Handbook on Loss Reserving 2016 (Paperback, 2016 ed.)
Michael Radtke, Klaus D. Schmidt, Anja Schnaus
R1,033 Discovery Miles 10 330 Shipped within 20 - 25 working days

This handbook presents the basic aspects of actuarial loss reserving. Besides the traditional methods, it also includes a description of more recent ones and a discussion of certain problems occurring in actuarial practice, like inflation, scarce data, large claims, slow loss development, the use of market statistics, the need for simulation techniques and the task of calculating best estimates and ranges of future losses. In property and casualty insurance the provisions for payment obligations from losses that have occurred but have not yet been settled usually constitute the largest item on the liabilities side of an insurer's balance sheet. For this reason, the determination and evaluation of these loss reserves is of considerable economic importance for every property and casualty insurer. Actuarial students, academics as well as practicing actuaries will benefit from this overview of the most important actuarial methods of loss reserving by developing an understanding of the underlying stochastic models and how to practically solve some problems which may occur in actuarial practice.

The Cambridge Dictionary of Probability and its Applications (Hardcover): David Stirzaker The Cambridge Dictionary of Probability and its Applications (Hardcover)
David Stirzaker
R2,964 Discovery Miles 29 640 Shipped within 20 - 25 working days

Probability comes of age with this, the first dictionary of probability and its applications in English, which supplies a guide to the concepts and vocabulary of this rapidly expanding field. Besides the basic theory of probability and random processes, applications covered here include financial and insurance mathematics, operations research (including queueing, reliability, and inventories), decision and game theory, optimization, time series, networks, and communication theory, as well as classic problems and paradoxes. The dictionary is reliable, stable, concise, and cohesive. Each entry provides a rigorous definition, a sketch of the context, and a reference pointing the reader to the wider literature. Judicious use of figures makes complex concepts easier to follow without oversimplifying. As the only dictionary on the market, this will be a guiding reference for all those working in, or learning, probability together with its applications.

Semigroups of Linear Operators - With Applications to Analysis, Probability and Physics (Paperback): David Applebaum Semigroups of Linear Operators - With Applications to Analysis, Probability and Physics (Paperback)
David Applebaum
R625 Discovery Miles 6 250 Shipped within 20 - 25 working days

The theory of semigroups of operators is one of the most important themes in modern analysis. Not only does it have great intellectual beauty, but also wide-ranging applications. In this book the author first presents the essential elements of the theory, introducing the notions of semigroup, generator and resolvent, and establishes the key theorems of Hille-Yosida and Lumer-Phillips that give conditions for a linear operator to generate a semigroup. He then presents a mixture of applications and further developments of the theory. This includes a description of how semigroups are used to solve parabolic partial differential equations, applications to Levy and Feller-Markov processes, Koopmanism in relation to dynamical systems, quantum dynamical semigroups, and applications to generalisations of the Riemann-Liouville fractional integral. Along the way the reader encounters several important ideas in modern analysis including Sobolev spaces, pseudo-differential operators and the Nash inequality.

Introduction to Probability Models (Hardcover, 12th edition): Sheldon M. Ross Introduction to Probability Models (Hardcover, 12th edition)
Sheldon M. Ross
R2,217 R1,753 Discovery Miles 17 530 Save R464 (21%) Shipped within 20 - 25 working days

Introduction to Probability Models, Twelfth Edition, is the latest version of Sheldon Ross's classic bestseller. This trusted book introduces the reader to elementary probability modelling and stochastic processes and shows how probability theory can be applied in fields such as engineering, computer science, management science, the physical and social sciences and operations research. The hallmark features of this text have been retained in this edition, including a superior writing style and excellent exercises and examples covering the wide breadth of coverage of probability topics. In addition, many real-world applications in engineering, science, business and economics are included.

Introduction to Stochastic Processes with R (Hardcover): Robert P. Dobrow Introduction to Stochastic Processes with R (Hardcover)
Robert P. Dobrow
R2,322 R2,079 Discovery Miles 20 790 Save R243 (10%) Shipped within 20 - 25 working days

An introduction to stochastic processes through the use of R Introduction to Stochastic Processes with R is an accessible and well-balanced presentation of the theory of stochastic processes, with an emphasis on real-world applications of probability theory in the natural and social sciences. The use of simulation, by means of the popular statistical software R, makes theoretical results come alive with practical, hands-on demonstrations. Written by a highly-qualified expert in the field, the author presents numerous examples from a wide array of disciplines, which are used to illustrate concepts and highlight computational and theoretical results. Developing readers problem-solving skills and mathematical maturity, Introduction to Stochastic Processes with R features: * More than 200 examples and 600 end-of-chapter exercises * A tutorial for getting started with R, and appendices that contain review material in probability and matrix algebra * Discussions of many timely and stimulating topics including Markov chain Monte Carlo, random walk on graphs, card shuffling, Black Scholes options pricing, applications in biology and genetics, cryptography, martingales, and stochastic calculus * Introductions to mathematics as needed in order to suit readers at many mathematical levels * A companion web site that includes relevant data files as well as all R code and scripts used throughout the book Introduction to Stochastic Processes with R is an ideal textbook for an introductory course in stochastic processes. The book is aimed at undergraduate and beginning graduate-level students in the science, technology, engineering, and mathematics disciplines. The book is also an excellent reference for applied mathematicians and statisticians who are interested in a review of the topic.

The Probability Companion for Engineering and Computer Science (Hardcover): Adam Prugel-Bennett The Probability Companion for Engineering and Computer Science (Hardcover)
Adam Prugel-Bennett
R2,395 Discovery Miles 23 950 Shipped within 20 - 25 working days

This friendly guide is the companion you need to convert pure mathematics into understanding and facility with a host of probabilistic tools. The book provides a high-level view of probability and its most powerful applications. It begins with the basic rules of probability and quickly progresses to some of the most sophisticated modern techniques in use, including Kalman filters, Monte Carlo techniques, machine learning methods, Bayesian inference and stochastic processes. It draws on thirty years of experience in applying probabilistic methods to problems in computational science and engineering, and numerous practical examples illustrate where these techniques are used in the real world. Topics of discussion range from carbon dating to Wasserstein GANs, one of the most recent developments in Deep Learning. The underlying mathematics is presented in full, but clarity takes priority over complete rigour, making this text a starting reference source for researchers and a readable overview for students.

Probabilistic Models of Population Evolution - Scaling Limits, Genealogies and Interactions (Paperback, 1st ed. 2016): Etienne... Probabilistic Models of Population Evolution - Scaling Limits, Genealogies and Interactions (Paperback, 1st ed. 2016)
Etienne Pardoux
R726 R689 Discovery Miles 6 890 Save R37 (5%) Shipped within 20 - 25 working days

This expository book presents the mathematical description of evolutionary models of populations subject to interactions (e.g. competition) within the population. The author includes both models of finite populations, and limiting models as the size of the population tends to infinity. The size of the population is described as a random function of time and of the initial population (the ancestors at time 0). The genealogical tree of such a population is given. Most models imply that the population is bound to go extinct in finite time. It is explained when the interaction is strong enough so that the extinction time remains finite, when the ancestral population at time 0 goes to infinity. The material could be used for teaching stochastic processes, together with their applications. Etienne Pardoux is Professor at Aix-Marseille University, working in the field of Stochastic Analysis, stochastic partial differential equations, and probabilistic models in evolutionary biology and population genetics. He obtained his PhD in 1975 at University of Paris-Sud.

Mathematics of Two-Dimensional Turbulence (Hardcover, New): Sergei B. Kuksin, Armen Shirikyan Mathematics of Two-Dimensional Turbulence (Hardcover, New)
Sergei B. Kuksin, Armen Shirikyan
R1,487 R1,382 Discovery Miles 13 820 Save R105 (7%) Shipped within 20 - 25 working days

This book is dedicated to the mathematical study of two-dimensional statistical hydrodynamics and turbulence, described by the 2D Navier-Stokes system with a random force. The authors' main goal is to justify the statistical properties of a fluid's velocity field u(t,x) that physicists assume in their work. They rigorously prove that u(t,x) converges, as time grows, to a statistical equilibrium, independent of initial data. They use this to study ergodic properties of u(t,x) - proving, in particular, that observables f(u(t,.)) satisfy the strong law of large numbers and central limit theorem. They also discuss the inviscid limit when viscosity goes to zero, normalising the force so that the energy of solutions stays constant, while their Reynolds numbers grow to infinity. They show that then the statistical equilibria converge to invariant measures of the 2D Euler equation and study these measures. The methods apply to other nonlinear PDEs perturbed by random forces.

A First Course in Stochastic Models (Hardcover, 2 Rev Ed): Henk C. Tijms A First Course in Stochastic Models (Hardcover, 2 Rev Ed)
Henk C. Tijms
R1,251 R1,139 Discovery Miles 11 390 Save R112 (9%) Shipped within 20 - 25 working days

The field of applied probability has changed profoundly in the past twenty years. The development of computational methods has greatly contributed to a better understanding of the theory. A First Course in Stochastic Models provides a self-contained introduction to the theory and applications of stochastic models. Emphasis is placed on establishing the theoretical foundations of the subject, thereby providing a framework in which the applications can be understood. Without this solid basis in theory no applications can be solved.

  • Provides an introduction to the use of stochastic models through an integrated presentation of theory, algorithms and applications.

  • Incorporates recent developments in computational probability.

  • Includes a wide range of examples that illustrate the models and make the methods of solution clear.

  • Features an abundance of motivating exercises that help the student learn how to apply the theory.

  • Accessible to anyone with a basic knowledge of probability.
A First Course in Stochastic Models is suitable for senior undergraduate and graduate students from computer science, engineering, statistics, operations research, and any other discipline where stochastic modelling takes place. It stands out amongst other textbooks on the subject because of its integrated presentation of theory, algorithms and applications.
An Introduction to Stochastic Dynamics (Paperback): Jinqiao Duan An Introduction to Stochastic Dynamics (Paperback)
Jinqiao Duan
R1,080 Discovery Miles 10 800 Shipped within 20 - 25 working days

The mathematical theory of stochastic dynamics has become an important tool in the modeling of uncertainty in many complex biological, physical, and chemical systems and in engineering applications - for example, gene regulation systems, neuronal networks, geophysical flows, climate dynamics, chemical reaction systems, nanocomposites, and communication systems. It is now understood that these systems are often subject to random influences, which can significantly impact their evolution. This book serves as a concise introductory text on stochastic dynamics for applied mathematicians and scientists. Starting from the knowledge base typical for beginning graduate students in applied mathematics, it introduces the basic tools from probability and analysis and then develops for stochastic systems the properties traditionally calculated for deterministic systems. The book's final chapter opens the door to modeling in non-Gaussian situations, typical of many real-world applications. Rich with examples, illustrations, and exercises with solutions, this book is also ideal for self-study.

Stochastic Tools in Turbulence (Paperback): John L. Lumley Stochastic Tools in Turbulence (Paperback)
John L. Lumley
R248 R201 Discovery Miles 2 010 Save R47 (19%) 17 working days

This accessible treatment offers the mathematical tools for describing and solving problems related to stochastic vector fields. Advanced undergraduates and graduate students will find its use of generalized functions a relatively simple method of resolving mathematical questions. It will prove a valuable reference for applied mathematicians and professionals in the fields of aerospace, chemical, civil, and nuclear engineering.
The author, Professor Emeritus of Engineering at Cornell University, starts with a survey of probability distributions and densities and proceeds to examinations of moments, characteristic functions, and the Gaussian distribution; random functions; and random processes in more dimensions. Extensive appendixes--which include information on Fourier transforms, tensors, generalized functions, and invariant theory--contribute toward making this volume mathematically self-contained.

Stochastic Analysis - Ito and Malliavin Calculus in Tandem (Hardcover): Hiroyuki Matsumoto, Setsuo Taniguchi Stochastic Analysis - Ito and Malliavin Calculus in Tandem (Hardcover)
Hiroyuki Matsumoto, Setsuo Taniguchi
R1,235 R1,171 Discovery Miles 11 710 Save R64 (5%) Shipped within 20 - 25 working days

Thanks to the driving forces of the Ito calculus and the Malliavin calculus, stochastic analysis has expanded into numerous fields including partial differential equations, physics, and mathematical finance. This book is a compact, graduate-level text that develops the two calculi in tandem, laying out a balanced toolbox for researchers and students in mathematics and mathematical finance. The book explores foundations and applications of the two calculi, including stochastic integrals and differential equations, and the distribution theory on Wiener space developed by the Japanese school of probability. Uniquely, the book then delves into the possibilities that arise by using the two flavors of calculus together. Taking a distinctive, path-space-oriented approach, this book crystallizes modern day stochastic analysis into a single volume.

Martingales in Banach Spaces (Hardcover): Gilles Pisier Martingales in Banach Spaces (Hardcover)
Gilles Pisier
R1,323 R1,253 Discovery Miles 12 530 Save R70 (5%) Shipped within 20 - 25 working days

This book focuses on the major applications of martingales to the geometry of Banach spaces, and a substantial discussion of harmonic analysis in Banach space valued Hardy spaces is also presented. It covers exciting links between super-reflexivity and some metric spaces related to computer science, as well as an outline of the recently developed theory of non-commutative martingales, which has natural connections with quantum physics and quantum information theory. Requiring few prerequisites and providing fully detailed proofs for the main results, this self-contained study is accessible to graduate students with a basic knowledge of real and complex analysis and functional analysis. Chapters can be read independently, with each building from the introductory notes, and the diversity of topics included also means this book can serve as the basis for a variety of graduate courses.

Nonlinear Economic Models - Cross-sectional, Time Series and Neural Network Applications (Hardcover): John Creedy, Vance L.... Nonlinear Economic Models - Cross-sectional, Time Series and Neural Network Applications (Hardcover)
John Creedy, Vance L. Martin
R2,587 Discovery Miles 25 870 Shipped within 20 - 25 working days

Nonlinear modelling has become increasingly important and widely used in economics. This valuable book brings together recent advances in the area including contributions covering cross-sectional studies of income distribution and discrete choice models, time series models of exchange rate dynamics and jump processes, and artificial neural network and genetic algorithm models of financial markets. Attention is given to the development of theoretical models as well as estimation and testing methods with a wide range of applications in micro and macroeconomics, labour and finance. The book provides valuable introductory material that is accessible to students and scholars interested in this exciting research area, as well as presenting the results of new and original research. Nonlinear Economic Models provides a sequel to Chaos and Nonlinear Models in Economics by the same editors.

Modeling Random Processes for Engineers and Managers (Hardcover): James J. Solberg Modeling Random Processes for Engineers and Managers (Hardcover)
James J. Solberg
R3,840 Discovery Miles 38 400 Shipped within 20 - 25 working days

By reducing mathematical detail and focusing on real-world applications, this book provides engineers with an easy-to-understand overview of stochastic modeling. An entire chapter is included on how to set up the problem, and then another complete chapter presents examples of applications before doing any math. A previously unpublished computational method for solving equations related to Markov processes is added. The book shows how to add costs or revenues to the basic probability structures without much additional effort. In addition, numerous examples are included that show how the theory can be used. Engineers will also find explanations on how to formulate word problems into the models that the math worked on.

Weakly Stationary Random Fields, Invariant Subspaces and Applications (Hardcover): Vidyadhar S. Mandrekar, David A. Redett Weakly Stationary Random Fields, Invariant Subspaces and Applications (Hardcover)
Vidyadhar S. Mandrekar, David A. Redett
R2,674 Discovery Miles 26 740 Shipped within 20 - 25 working days

The first book to examine weakly stationary random fields and their connections with invariant subspaces (an area associated with functional analysis). It reviews current literature, presents central issues and most important results within the area. For advanced Ph.D. students, researchers, especially those conducting research on Gaussian theory.

Markov Processes and Applications - Algorithms, Networks, Genome and Finance (Hardcover): Etienne Pardoux Markov Processes and Applications - Algorithms, Networks, Genome and Finance (Hardcover)
Etienne Pardoux
R1,521 R1,374 Discovery Miles 13 740 Save R147 (10%) Shipped within 20 - 25 working days

"This well-written book provides a clear and accessible treatment of the theory of discrete and continuous-time Markov chains, with an emphasis towards applications. The mathematical treatment is precise and rigorous without superfluous details, and the results are immediately illustrated in illuminating examples. This book will be extremely useful to anybody teaching a course on Markov processes.""
Jean-Francois Le Gall, Professor at Universite de Paris-Orsay, France."

Markov processes is the class of stochastic processes whose past and future are conditionally independent, given their present state. They constitute important models in many applied fields.

After an introduction to the Monte Carlo method, this book describes discrete time Markov chains, the Poisson process and continuous time Markov chains. It also presents numerous applications including Markov Chain Monte Carlo, Simulated Annealing, Hidden Markov Models, Annotation and Alignment of Genomic sequences, Control and Filtering, Phylogenetic tree reconstruction and Queuing networks. The last chapter is an introduction to stochastic calculus and mathematical finance.

Features include:

The Monte Carlo method, discrete time Markov chains, the Poisson process and continuous time jump Markov processes.An introduction to diffusion processes, mathematical finance and stochastic calculus.Applications of Markov processes to various fields, ranging from mathematical biology, to financial engineering and computer science.Numerous exercises and problems with solutions to most of them

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