An Iterative Linearised Solution to the Sinusoidal Parameter Estimation   Problem
  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. 
Jean-Marc Valin, Daniel V. Smith, Christopher Montgomery, Timothy B.   Terriberry
cs.SD