Kontakt
Ako nakupovať
Doručenie
Nákupný poradca
Angličtina
159 b
Až 30 dní na vrátenie tovaru
Zákazníci tiež kúpili
This book was published in 2004. The estimation of noisily observed states from a sequence of data has traditionally incorporated ideas from Hilbert spaces and calculus-based probability theory. As conditional expectation is the key concept, the correct setting for filtering theory is that of a probability space. Graduate engineers, mathematicians and those working in quantitative finance wishing to use filtering techniques will find in the first half of this book an accessible introduction to measure theory, stochastic calculus, and stochastic processes, with particular emphasis on martingales and Brownian motion. Exercises are included. The book then provides an excellent users' guide to filtering: basic theory is followed by a thorough treatment of Kalman filtering, including recent results which extend the Kalman filter to provide parameter estimates. These ideas are then applied to problems arising in finance, genetics and population modelling in three separate chapters, making this a comprehensive resource for both practitioners and researchers.
Informácie o knihe
Angličtina
Darujte túto knihu ešte dnes
Je to jednoduché
1 Pridajte knihu do košíka a vyberte možnosť doručiť ako darček 2 Obratom Vám zašleme poukaz 3 Knihu zašleme na adresu obdarovanéhoMohlo by vás tiež zaujímať
/
Brožovaná
30.70
€
/
Brožovaná
104.83
€
Ahoj! Som Libroamiko, tvoj knižný radca.
Ako ti môžem pomôcť?