  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.
