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An iterative linearised solution to the sinusoidal parameter estimation problem. (English) Zbl 1195.94036

Summary: Signal processing applications use sinusoidal modelling for speech synthesis, speech coding, and audio coding. Estimation of the model parameters involves non-linear optimisation methods, which can be very costly for real-time applications. We propose a low-complexity iterative method that starts from initial frequency estimates and converges rapidly. We show that for \(N\) sinusoids in a frame of length \(L\), the proposed method has a complexity of \(O(LN )\), which is significantly less than the matching pursuits method. Furthermore, the proposed method is shown to be more accurate than the matching pursuits and time-frequency reassignment methods in our experiments.

MSC:

94A12 Signal theory (characterization, reconstruction, filtering, etc.)