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. Key words: Sinusoidal modeling, iterative least-squares solution

• Type: Journal
• Year: 2010
• Where: CEE
• Authors: Jean-Marc Valin, Daniel V. Smith, Christopher Montgomery, Timothy B. Terriberry
• Keywords: CEE 2010, Low-complexity Iterative Method, Non-linear Optimisation Methods, Signal Processing Applications