MARC details
| 000 -LEADER |
|---|
| fixed length control field |
04370cam a2200421 i 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20250919002744.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
150317s2012 flua bi 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781420094602 |
| Qualifying information |
(hardcover) |
| Terms of availability |
RM388.44 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
1420094602 |
| Qualifying information |
(hardcover). |
| 039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE] |
|---|
| Level of rules in bibliographic description |
201506040923 |
| Level of effort used to assign nonsubject heading access points |
lan |
| Level of effort used to assign subject headings |
201506040922 |
| Level of effort used to assign classification |
lan |
| Level of effort used to assign subject headings |
201506021434 |
| Level of effort used to assign classification |
haiyati |
| Level of effort used to assign subject headings |
201506021431 |
| Level of effort used to assign classification |
haiyati |
| y |
03-17-2015 |
| z |
hamudah |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
DNLM/DLC |
| Language of cataloging |
eng |
| Transcribing agency |
DLC |
| Modifying agency |
YDX |
| -- |
BTCTA |
| -- |
BAKER |
| -- |
YDXCP |
| -- |
NLM |
| -- |
UKMGB |
| -- |
CDX |
| -- |
NJI |
| -- |
UKM |
| Description conventions |
rda |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
|---|
| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
RC386.6.O933 |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
|---|
| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
RC386.6 |
| Local cutter number (OCLC) ; Book number/undivided call number, CALL (RLIN) |
.O933 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Ozaki, Tohru, |
| Dates associated with a name |
1944- |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Time series modeling of neuroscience data / |
| Statement of responsibility, etc. |
Tohru Ozaki. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Boca Raton : |
| Name of producer, publisher, distributor, manufacturer |
Taylor & Francis, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2012. |
| 264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
©2012. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxv, 548 pages : |
| Other physical details |
illustrations ; |
| Dimensions |
25 cm. |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
unmediated |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
volume |
| Source |
rdacarrier |
| 490 1# - SERIES STATEMENT |
|---|
| Series statement |
Chapman & Hall/CRC interdisciplinary statistics. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references (p. 519-532) and index. |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Introduction -- Part I: Dynamic models for time series prediction -- Time series prediction and the power spectrum -- Discrete-time dynamic models -- Multivariate dynamic models -- Continuous-time dynamic models -- Some more models -- Part II: Related theories and tools -- Prediction and Doob decomposition -- Dynamics and stationary distributions -- Bridge between continuous-time models and discrete-time models -- Liklelihood of dynamic models -- Part III: State space modeling -- Inference problem (a) for state models -- Inference problem (b) for state space models -- Art of likelihood maximization -- Casuality analysis -- Conclusion : the new and old problems. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
'Recent advances in brain science measurement technology have given researchers access to very large-scale time series data such as EEG/MEG data (20 to 100 dimensional) and fMRI (140,000 dimensional) data. To analyze such massive data, efficient computational and statistical methods are required. Time Series Modeling of Neuroscience Data shows how to efficiently analyze neuroscience data by the Wiener-Kalman-Akaike approach, in which dynamic models of all kinds, such as linear/nonlinear differential equation models and time series models, are used for whitening the temporally dependent time series in the framework of linear/nonlinear state space models. Using as little mathematics as possible, this book explores some of its basic concepts and their derivatives as useful tools for time series analysis. Unique features include: statistical identification method of highly nonlinear dynamical systems such as the Hodgkin-Huxley model, Lorenz chaos model, Zetterberg Model, and more Methods and applications for Dynamic Causality Analysis developed by Wiener, Granger, and Akaike state space modeling method for dynamicization of solutions for the Inverse Problems heteroscedastic state space modeling method for dynamic non-stationary signal decomposition for applications to signal detection problems in EEG data analysis An innovation-based method for the characterization of nonlinear and/or non-Gaussian time series An innovation-based method for spatial time series modeling for fMRI data analysis The main point of interest in this book is to show that the same data can be treated using both a dynamical system and time series approach so that the neural and physiological information can be extracted more efficiently. Of course, time series modeling is valid not only in neuroscience data analysis but also in many other sciences and engineering fields where the statistical inference from the observed time series data plays an important role'--Provided by publisher. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Nervous system |
| General subdivision |
Diseases |
| -- |
Diagnosis |
| -- |
Statistical methods. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Brain mapping |
| General subdivision |
Statistical methods. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Neurosciences |
| General subdivision |
Statistics. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Chapman & Hall/CRC interdisciplinary statistics. |
| 907 ## - LOCAL DATA ELEMENT G, LDG (RLIN) |
|---|
| a |
.b16095911 |
| b |
2019-11-12 |
| c |
2019-11-12 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
AM |
| Suppress in OPAC |
No |
| Call number prefix |
RC386.6.O933 |
| 914 ## - VTLS Number |
|---|
| VTLS Number |
vtls003581082 |
| 990 ## - EQUIVALENCES OR CROSS-REFERENCES [LOCAL, CANADA] |
|---|
| Link information for 9XX fields |
nh |
| 991 ## - LOCAL NOTE (NAMA FAKULTI/INSTITUT/PUSAT) |
|---|
| a |
Fakulti Sains dan Teknologi |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) |
|---|
| Library |
PERPUSTAKAAN TUN SERI LANANG |
| Operator's initials, OID (RLIN) |
2015-04-03 |
| Cataloger's initials, CIN (RLIN) |
m |
| Material Type (Sierra) |
Printed Books |
| Language |
English |
| Country |
|
| -- |
0 |
| -- |
.b16095911 |
