Modern logic has been intimately connected with algebra since its origins in figures such as Boole, De Morgan, and Peirce. ...
WeiterlesenThe sources of new ideas and methods include practical developments in areas such as neural networks, quantum computation, ...
WeiterlesenThis book deals with the differential geometry of manifolds, loop spaces, line bundles and groupoids, and the relations of ...
WeiterlesenThis book contains a detailed and complete demonstration of the existence of an equivariate isomorphism between the Lubin-Tate ...
WeiterlesenIt provides a complete and systematic introduction to the fundamentals of the hyperequational theory of universal algebra, ...
WeiterlesenIt provides a complete and systematic introduction to the fundamentals of the hyperequational theory of universal algebra, ...
WeiterlesenThe Scottish mathematician Colin MacLaurin (1698-1746) is best known for developing and extending Newton’s work in calculus, ...
WeiterlesenThis book presents the main mathematical machines for drawing curves, for applying geometrical transformations or for making ...
WeiterlesenThis book presents the main mathematical machines for drawing curves, for applying geometrical transformations or for making ...
WeiterlesenThis three volume book set constitutes the proceedings of the Third International Conference on Machine Learning for Cyber ...
WeiterlesenThis three volume book set constitutes the proceedings of the Third International Conference on Machine Learning for Cyber ...
WeiterlesenWhile the original works on Malliavin calculus aimed to study the smoothness of densities of solutions to stochastic differential ...
Weiterlesenthe history of mathematics there are many situations in which cal- lations were performed incorrectly for important practical ...
WeiterlesenIt is a challenging task to read the balance sheet of an insurance company. This derives from the fact that different positions ...
WeiterlesenMarkov chains are a particularly powerful and widely used tool for analyzing a variety of stochastic (probabilistic) systems ...
WeiterlesenMarkov chains are a particularly powerful and widely used tool for analyzing a variety of stochastic (probabilistic) systems ...
WeiterlesenMarkov decision processes (MDPs), also called stochastic dynamic programming, were first studied in the 1960s. MDPs can be ...
WeiterlesenThe book consists of two parts. Part I,This part introduces strong Markov processes and their potential theory. In particular,it ...
WeiterlesenThis book provides a comprehensive, self-contained and up-to-date treatment of the main topics in the theory of option pricing. ...
WeiterlesenThis book is entirely devoted to discrete time and provides a detailed introduction to the construction of the rigorous mathematical ...
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