Yuneisy Garcia Guzman, Michael Lunglmayr, Mario Huemer,
"A Gradient Ascent Approach for Multiple Frequency Estimation"
: Computer Aided Systems Theory - EUROCAST 2019, Part II, Lecture Notes in Computer Science (LNCS), Serie Lecture Notes in Computer Science (LNCS), Vol. 12014, Springer, Seite(n) 20-27, 4-2020, ISBN: 978-3-030-45096-0
Original Titel:
A Gradient Ascent Approach for Multiple Frequency Estimation
Sprache des Titels:
Englisch
Original Buchtitel:
Computer Aided Systems Theory - EUROCAST 2019, Part II, Lecture Notes in Computer Science (LNCS)
Original Kurzfassung:
This work investigates a new approach for frequency estimation of multiple complex sinusoids in the presence of noise. The algorithm is based on the optimization of the least squares (LS) cost function using a gradient ascent algorithm. The paper studies the performance of the
proposed method and compares it to other estimation techniques such as root-multiple signal classification (root-MUSIC) and the discrete-time Fourier transform (DTFT). Simulation results show the performance gains provided by the proposed algorithm in different scenarios.
Forschungs-