Sparse Semi-Parametric Estimation of Harmonic Chirp Signals
نویسندگان
چکیده
منابع مشابه
Parameter Estimation of Chirp Signals PETAR
The problem of the parameter estimation of chirp signals is addressed. Several closely related estimators are proposed whose main characteristics are simplicity, accuracy, and ease of on-line or off-line implementation. For moderately high signal-to-noise ratios they are unbiased and attain the Cramer-Rao bound. Monte Carlo simulations verify the expected performance of the estimators.
متن کاملSemi-parametric estimation of the strategic goods (OPEC oil price)
In the global economy, crude oil is among the most important strategic goods that affects the performance of local and international markets. Prediction of the oil price has always been an important challenging topic in the global economy and producers and consumers have constantly been trying to improve their roll in the oil price changes and for many years OPEC has been one of the key players...
متن کاملParameter estimation for random amplitude chirp signals
We consider the problem of estimating the parameters of a chirp signal observed in multiplicative noise, i.e., whose amplitude is randomly time-varying. Two methods for solving this problem are presented. First, an unstructured nonlinear least-squares approach (NLS) is proposed. It is shown that by minimizing the NLS criterion with respect to all samples of the time-varying amplitude, the probl...
متن کاملCovariance-Based Direction-of-Arrival Estimation of Wideband Coherent Chirp Signals via Sparse Representation
This paper addresses the problem of direction-of-arrival (DOA) estimation of multiple wideband coherent chirp signals, and a new method is proposed. The new method is based on signal component analysis of the array output covariance, instead of the complicated time-frequency analysis used in previous literatures, and thus is more compact and effectively avoids possible signal energy loss during...
متن کاملHarmonic Tracking-based Short-Time Chirp Analysis of Speech Signals
The Short-Time Fourier Transform is the most popular timefrequency analysis tool applied in speech processing. This transform delivers fair quality analysis for periodic signals, but, since speech is quasi-periodic, the transform suffers from blurry harmonic representation when voiced speech undergoes changes in pitch. This frequency variation could be relative high in comparison with the analy...
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: IEEE Transactions on Signal Processing
سال: 2016
ISSN: 1053-587X,1941-0476
DOI: 10.1109/tsp.2015.2507538