2018Unpublished venueRequires access

An Iterative Algorithm for Dual-Frequency Signals With Unknown Frequencies and Amplitudes

Siyu Liu, Guanglei Song, Feng Ding

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Abstract

A new iterative parameter estimation algorithm is proposed to estimate all parameters of dual-frequency signals including the unknown amplitudes, frequencies and phases. The observation data of the signals are disturbed by stochastic noise. The key is that the signal model is a highly nonlinear function in regard to the frequencies and phases. A gradient-based iterative algorithm is presented to compare the algorithm performance. The performance of the proposed method is tested by simulation.

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What this paper is about

A new iterative parameter estimation algorithm is proposed to estimate all parameters of dual-frequency signals including the unknown amplitudes, frequencies and phases. The observation data of the signals are disturbed by stochastic noise. The key is that the signal model is a highly nonlinear function in regard to the frequencies and phases. A gradient-based iterative algorithm is presented to compare the algorithm performance. The performance of the proposed method is tested by simulation.

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Available abstract

A new iterative parameter estimation algorithm is proposed to estimate all parameters of dual-frequency signals including the unknown amplitudes, frequencies and phases. The observation data of the signals are disturbed by stochastic noise. The key is that the signal model is a highly nonlinear function in regard to the frequencies and phases. A gradient-based iterative algorithm is presented to compare the algorithm performance. The performance of the proposed method is tested by simulation.

Key concepts: Algorithm, Noise (video), Amplitude, Iterative method, Computer science, SIGNAL (programming language), Nonlinear system, Function (biology)

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