In this book we analyze the error caused by numerical schemes for the approximation of semilinear stochastic evolution equations (SEEq) in a Hilbert space-valued setting. The numerical schemes considered combine Galerkin finite element methods with Euler-type temporal approximations. Starting from a precise analysis of the spatio-temporal regularity of the mild solution to the SEEq, we derive and prove optimal error estimates of the strong error of convergence in the first part of the book.
The second part deals with a new approach to the so-called weak error of convergence, which measures the distance between the law of the numerical solution and the law of the exact solution. This approach is based on Bismut’s integration by parts formula and the Malliavin calculus for infinite dimensional stochastic processes. These techniques are developed and explained in a separate chapter, before the weak convergence is proven for linear SEEq.
"synopsis" may belong to another edition of this title.
In this book we analyze the error caused by numerical schemes for the approximation of semilinear stochastic evolution equations (SEEq) in a Hilbert space-valued setting. The numerical schemes considered combine Galerkin finite element methods with Euler-type temporal approximations. Starting from a precise analysis of the spatio-temporal regularity of the mild solution to the SEEq, we derive and prove optimal error estimates of the strong error of convergence in the first part of the book.
The second part deals with a new approach to the so-called weak error of convergence, which measures the distance between the law of the numerical solution and the law of the exact solution. This approach is based on Bismut’s integration by parts formula and the Malliavin calculus for infinite dimensional stochastic processes. These techniques are developed and explained in a separate chapter, before the weak convergence is proven for linear SEEq.
"About this title" may belong to another edition of this title.
US$ 2.64 shipping within U.S.A.
Destination, rates & speedsSeller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New. Seller Inventory # 20301997-n
Quantity: Over 20 available
Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
Condition: New. Seller Inventory # ABLIING23Mar3113020086199
Quantity: Over 20 available
Seller: California Books, Miami, FL, U.S.A.
Condition: New. Seller Inventory # I-9783319022307
Quantity: Over 20 available
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition. Seller Inventory # 20301997
Quantity: Over 20 available
Seller: Grand Eagle Retail, Mason, OH, U.S.A.
Paperback. Condition: new. Paperback. In this book we analyze the error caused by numerical schemes for the approximation of semilinear stochastic evolution equations (SEEq) in a Hilbert space-valued setting. The numerical schemes considered combine Galerkin finite element methods with Euler-type temporal approximations. Starting from a precise analysis of the spatio-temporal regularity of the mild solution to the SEEq, we derive and prove optimal error estimates of the strong error of convergence in the first part of the book.The second part deals with a new approach to the so-called weak error of convergence, which measures the distance between the law of the numerical solution and the law of the exact solution. This approach is based on Bismuts integration by parts formula and the Malliavin calculus for infinite dimensional stochastic processes. These techniques are developed and explained in a separate chapter, before the weak convergence is proven for linear SEEq. In this book we analyze the error caused by numerical schemes for the approximation of semilinear stochastic evolution equations (SEEq) in a Hilbert space-valued setting. The numerical schemes considered combine Galerkin finite element methods with Euler-type temporal approximations. Starting from a precise analysis of the spatio-temporal regularity of the mild solution to the SEEq, we derive and prove optimal error estimates of the strong error of convergence in the first part of the book.The second part deals with a new approach to the so-called weak error of convergence, which measures the distance between the law of the numerical solution and the law of the exact solution. This approach is based on Bismut's integration by parts formula and the Malliavin calculus for infinite dimensional stochastic processes. These techniques are developed and explained in a separate chapter, before the weak convergence is proven for linear SEEq. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9783319022307
Quantity: 1 available
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. pp. 196. Seller Inventory # 2697863050
Quantity: 4 available
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Condition: New. In. Seller Inventory # ria9783319022307_new
Quantity: Over 20 available
Seller: Chiron Media, Wallingford, United Kingdom
PF. Condition: New. Seller Inventory # 6666-IUK-9783319022307
Quantity: 10 available
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. Print on Demand pp. 196 4 Illus. Seller Inventory # 94566997
Quantity: 4 available
Seller: Libro Co. Italia Srl, San Casciano Val di Pesa, FI, Italy
Brossura. Condition: fine. Heidelberg, 2013; br., pp. 196, cm 23,5x15,5. Libro. Seller Inventory # 1664639
Quantity: 1 available