語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Dynamic systems models = new methods...
~
Borodovsky, Mark.
FindBook
Google Book
Amazon
博客來
Dynamic systems models = new methods of parameter and state estimation /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Dynamic systems models/ by Josif A. Boguslavskiy ; edited by Mark Borodovsky.
其他題名:
new methods of parameter and state estimation /
作者:
Boguslavskiy, Josif A.
其他作者:
Borodovsky, Mark.
出版者:
Cham :Springer International Publishing : : 2016.,
面頁冊數:
xx, 201 p. :ill., digital ;24 cm.
內容註:
From the Contents: Linear Estimators of a Random-Parameter Vector -- Basis of the Method of Polynomial Approximation -- Polynomial Approximation and Optimization of Control -- Polynomial Approximation Technique Applied to Inverse Vector Functions -- Identification of Parameters of Nonlinear Dynamical Systems: Smoothing, Filtering and Forecasting the State Vector -- Estimating Status Vectors from Sight Angles -- Estimation of Parameters of Stochastic Models -- Designing the Control of Motion to a Target Point of Phase Space -- Inverse Problems of Dynamics Algorithm for Identifying Parameters of an Aircraft.
Contained By:
Springer eBooks
標題:
Estimation theory. -
電子資源:
http://dx.doi.org/10.1007/978-3-319-04036-3
ISBN:
9783319040363
Dynamic systems models = new methods of parameter and state estimation /
Boguslavskiy, Josif A.
Dynamic systems models
new methods of parameter and state estimation /[electronic resource] :by Josif A. Boguslavskiy ; edited by Mark Borodovsky. - Cham :Springer International Publishing :2016. - xx, 201 p. :ill., digital ;24 cm.
From the Contents: Linear Estimators of a Random-Parameter Vector -- Basis of the Method of Polynomial Approximation -- Polynomial Approximation and Optimization of Control -- Polynomial Approximation Technique Applied to Inverse Vector Functions -- Identification of Parameters of Nonlinear Dynamical Systems: Smoothing, Filtering and Forecasting the State Vector -- Estimating Status Vectors from Sight Angles -- Estimation of Parameters of Stochastic Models -- Designing the Control of Motion to a Target Point of Phase Space -- Inverse Problems of Dynamics Algorithm for Identifying Parameters of an Aircraft.
This monograph is an exposition of a novel method for solving inverse problems, a method of parameter estimation for time series data collected from simulations of real experiments. These time series might be generated by measuring the dynamics of aircraft in flight, by the function of a hidden Markov model used in bioinformatics or speech recognition or when analyzing the dynamics of asset pricing provided by the nonlinear models of financial mathematics. Dynamic Systems Models demonstrates the use of algorithms based on polynomial approximation which have weaker requirements than already-popular iterative methods. Specifically, they do not require a first approximation of a root vector and they allow non-differentiable elements in the vector functions being approximated. The text covers all the points necessary for the understanding and use of polynomial approximation from the mathematical fundamentals, through algorithm development to the application of the method in, for instance, aeroplane flight dynamics or biological sequence analysis. The technical material is illustrated by the use of worked examples and methods for training the algorithms are included. Dynamic Systems Models provides researchers in aerospatial engineering, bioinformatics and financial mathematics (as well as computer scientists interested in any of these fields) with a reliable and effective numerical method for nonlinear estimation and solving boundary problems when carrying out control design. It will also be of interest to academic researchers studying inverse problems and their solution.
ISBN: 9783319040363
Standard No.: 10.1007/978-3-319-04036-3doiSubjects--Topical Terms:
565962
Estimation theory.
LC Class. No.: QA276.8
Dewey Class. No.: 519.544
Dynamic systems models = new methods of parameter and state estimation /
LDR
:03219nmm m2200325 m 4500
001
2032860
003
DE-He213
005
20160922151857.0
006
m d
007
cr nn 008maaau
008
161011s2016 gw s 0 eng d
020
$a
9783319040363
$q
(electronic bk.)
020
$a
9783319040356
$q
(paper)
024
7
$a
10.1007/978-3-319-04036-3
$2
doi
035
$a
978-3-319-04036-3
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA276.8
072
7
$a
PBWR
$2
bicssc
072
7
$a
PHDT
$2
bicssc
072
7
$a
SCI012000
$2
bisacsh
082
0 4
$a
519.544
$2
23
090
$a
QA276.8
$b
.B675 2016
100
1
$a
Boguslavskiy, Josif A.
$3
2187074
245
1 0
$a
Dynamic systems models
$h
[electronic resource] :
$b
new methods of parameter and state estimation /
$c
by Josif A. Boguslavskiy ; edited by Mark Borodovsky.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2016.
300
$a
xx, 201 p. :
$b
ill., digital ;
$c
24 cm.
505
0
$a
From the Contents: Linear Estimators of a Random-Parameter Vector -- Basis of the Method of Polynomial Approximation -- Polynomial Approximation and Optimization of Control -- Polynomial Approximation Technique Applied to Inverse Vector Functions -- Identification of Parameters of Nonlinear Dynamical Systems: Smoothing, Filtering and Forecasting the State Vector -- Estimating Status Vectors from Sight Angles -- Estimation of Parameters of Stochastic Models -- Designing the Control of Motion to a Target Point of Phase Space -- Inverse Problems of Dynamics Algorithm for Identifying Parameters of an Aircraft.
520
$a
This monograph is an exposition of a novel method for solving inverse problems, a method of parameter estimation for time series data collected from simulations of real experiments. These time series might be generated by measuring the dynamics of aircraft in flight, by the function of a hidden Markov model used in bioinformatics or speech recognition or when analyzing the dynamics of asset pricing provided by the nonlinear models of financial mathematics. Dynamic Systems Models demonstrates the use of algorithms based on polynomial approximation which have weaker requirements than already-popular iterative methods. Specifically, they do not require a first approximation of a root vector and they allow non-differentiable elements in the vector functions being approximated. The text covers all the points necessary for the understanding and use of polynomial approximation from the mathematical fundamentals, through algorithm development to the application of the method in, for instance, aeroplane flight dynamics or biological sequence analysis. The technical material is illustrated by the use of worked examples and methods for training the algorithms are included. Dynamic Systems Models provides researchers in aerospatial engineering, bioinformatics and financial mathematics (as well as computer scientists interested in any of these fields) with a reliable and effective numerical method for nonlinear estimation and solving boundary problems when carrying out control design. It will also be of interest to academic researchers studying inverse problems and their solution.
650
0
$a
Estimation theory.
$3
565962
650
0
$a
Dynamics
$x
Mathematical models.
$3
566519
650
1 4
$a
Physics.
$3
516296
650
2 4
$a
Nonlinear Dynamics.
$3
608190
650
2 4
$a
Mathematical Modeling and Industrial Mathematics.
$3
891089
650
2 4
$a
Aerospace Technology and Astronautics.
$3
928116
650
2 4
$a
Signal, Image and Speech Processing.
$3
891073
650
2 4
$a
Quantitative Finance.
$3
891090
700
1
$a
Borodovsky, Mark.
$3
1085596
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer eBooks
856
4 0
$u
http://dx.doi.org/10.1007/978-3-319-04036-3
950
$a
Physics and Astronomy (Springer-11651)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9278929
電子資源
11.線上閱覽_V
電子書
EB QA276.8 .B675 2016
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入