Data-driven computational methods : (Record no. 65610)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01677nam a22001937a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 200611b2018 ||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781108472470 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 519.5 HAR-J |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Harlim, John |
| 245 ## - TITLE STATEMENT | |
| Title | Data-driven computational methods : |
| Remainder of title | parameter and operator estimations / |
| Statement of responsibility, etc. | John Harlim |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc. | United Kingdom |
| Name of publisher, distributor, etc. | Cambridge University Press |
| Date of publication, distribution, etc. | 2018 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 158 p. |
| 365 ## - TRADE PRICE | |
| Price type code | GBP |
| Price amount | 49.99. |
| 500 ## - GENERAL NOTE | |
| General note | Modern scientific computational methods are undergoing a transformative change; big data and statistical learning methods now have the potential to outperform the classical first-principles modeling paradigm. This book bridges this transition, connecting the theory of probability, stochastic processes, functional analysis, numerical analysis, and differential geometry. It describes two classes of computational methods to leverage data for modeling dynamical systems. The first is concerned with data fitting algorithms to estimate parameters in parametric models that are postulated on the basis of physical or dynamical laws. The second is on operator estimation, which uses the data to nonparametrically approximate the operator generated by the transition function of the underlying dynamical systems. This self-contained book is suitable for graduate studies in applied mathematics, statistics, and engineering. Carefully chosen elementary examples with supplementary MATLAB® codes and appendices covering the relevant prerequisite materials are provided, making it suitable for self-study. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Mathematical statistics |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Stochastic analysis |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer science |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Stochastic models |
| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) | |
| Withdrawn status | |
| Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Current library | Shelving location | Date acquired | Total Checkouts | Full call number | Barcode | Date last seen | Date last checked out | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | 510 | BITS Pilani Hyderabad | General Stack (For lending) | 11/06/2020 | 1 | 519.5 HAR-J | 41210 | 13/07/2024 | 11/01/2021 | Books |