Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

In this paper a fast method for blind identification of periodic sources is presented. In the well-known second order blind identification method, the information is extracted from instantaneous mixtures by simultaneously diagonalizing several time-delayed covariance matrices, however, the delays are chosen arbitrarily. This imposes computational cost which is linearly related to the number of covariance matrices. Statistical characteristics of periodic sources are exploited here to develop a method to effectively choose the appropriate delays in which the diagonalization takes place. Detail theory together with the corresponding theorems have been presented. Software simulations verify the superior performance of the algorithm in the face of different noise and frequency variation levels over alternative methods. © EURASIP, 2010.

Type

Conference paper

Publication Date

01/12/2010

Pages

1572 - 1576