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.
We consider the problem of sparse modeling of a signal consisting of an unknown number of exponentially decaying sinusoids. Since such signals are not sparse in an oversam-pled Fourier matrix, earlier approaches typically exploit large dictionary matrices that include not only a finely spaced frequency grid but also a grid over the considered damping factors. The resulting dictionary is often very...
Nuclear magnetic resonance (NMR) spectroscopy signals are ideally modelled as a superimposition of damped exponentials in additive Gaussian noise. In order to extract the information from these signals, methods are needed to decompose the signal into its components and estimate their parameters. This task can become quite difficult due to factors such as large number of samples, unknown and possibly...
In this study, we consider performance improvement of an array of fixed estimators by using stochastic design techniques. The optimal design is investigated both in the absence and presence of an average power constraint. Two different performance criteria are considered; the average Bayes risk and the maximum Bayes risk. It is shown that the optimal stochastic parameter design results in a randomization...
In statistical signal processing, hybrid parameter estimation refers to the case where the parameters vector to estimate contains both non-random and random parameters. In this communication, we propose a new hybrid lower bound which, for the first time, includes the Ziv-Zakaï bound well known for its tightness in the Bayesian context (random parameters only). For the general case of parameterized...
Modern high frequency (HF) over-the-horizon Radar's (OTHR's) that perform parametric sensing over a huge coverage of several million square kilometers operate in harsh sensing environments consisting of strong interference and clutter. The highly dynamic nature of such an environment governed by harsh ionosphere propagation conditions and a highly occupied HF spectrum mandate the application of adaptive...
This paper addresses the parameter estimation of multicomponent polynomial-phase signals (mc-PPSs). Recently proposed quasi-maximum likelihood (QML) method based on the short-time Fourier transform (STFT) has been extended to deal with multiple PPSs. The proposed method outperforms state-of-the-art parametric methods developed to deal with multiple PPSs in terms of robustness against noise, while...
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.