A closed-form identification of multichannel moving average processes by ESPRIT
نویسندگان
چکیده
منابع مشابه
A Closed-form Identification of Multichannel Moving Average Processes by Esprit*
In this paper, a closed-form identification of possibly nonrninimum phase multichannel moving average (MA) processes is derived by exploiting the eigenstructures of the observation cumulant matrices using ~the ESPRIT algorithm. The proposed approach allows the combination of statistics of different orders for better performance and offers reduced computation complexity when compared with existi...
متن کاملMoving Average Processes with Infinite Variance
The sample autocorrelation function (acf) of a stationary process has played a central statistical role in traditional time series analysis, where the assumption is made that the marginal distribution has a second moment. Now, the classical methods based on acf are not applicable in heavy tailed modeling. Using the codifference function as dependence measure for such processes be shown it be as...
متن کاملClosed-form multi-dimensional multi-invariance ESPRIT
A closed-form multi-dimensional multi-invariance generalization of the ESPRIT algorithm is introduced to exploit the entire invariance structure underlying a (possibly) multiparametric data model, thereby greatly improving estimation performance. The multiple-invariance data structure that this proposed method can handle includes: (1) multiple occurrence of one size of invariance along one or m...
متن کاملMoving Average Processes
JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. Blackwell Publishing and Royal Statistical Society are col...
متن کاملDe trending moving average algorithm: A closed-form approximation of the scaling law
The Hurst exponent H of long range correlated series can be estimated by means of the detrending moving average (DMA) method. The computational tool, on which the algorithm is based, is the generalized variance sDMA 1⁄4 1=ðN nÞ PN i1⁄4n1⁄2yðiÞ e ynðiÞ , with e ynðiÞ 1⁄4 1=nPnk1⁄40yði kÞ being the average over the moving window n and N the dimension of the stochastic series yðiÞ. The ability to ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Circuits, Systems, and Signal Processing
سال: 1996
ISSN: 0278-081X,1531-5878
DOI: 10.1007/bf01182591