The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Accurate and efficient estimation of the number of sources is critical for providing the parameter of targets in problems of array signal processing and blind source separation among other such problems. When conventional estimators work in unfavorable scenarios, e.g., at low signal-to-noise ratio (SNR), with a small number of snapshots, or for sources with a different strength, it is challenging...
The independent component analysis (ICA) is one of the most general methods for solving the blind signal separation. It gains lots of applications in communication, speech and medical science. When more sensors are used or the number of sources changes dynamically, natural gradient separation algorithm (NGSA) can solve the problem in a certain limit and the option of nonlinear function affects the...
The problem of blind despreading of the long-code direct sequence spread signal is addressed in this paper. A novel algorithm applicable in blind despreading algorithm of the long-code direct sequence spread spectrum signal is presented in this paper. The algorithm exploits the structure of the signal and a monotone missing-data model subject to low rank is constructed. Based on the maximum likelihood...
A blind synchronization algorithm for the direct sequence code division multiple access (DS-CDMA) signals is presented in this paper without knowledge of spreading sequence, carrier frequency, or the number of users. The only a priori information used is the symbol period. The algorithm exploits the structure of the signal correlation matrix and estimate the timing offset based on l1-norm of the correlation...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.