Multi-signal time-frequency model fitting using an approximate maximum likelihood algorithm
Ira J. Clarke · 2003
By taking advantage of the moderate computational demand of the recently developed approximate maximum likelihood (AML) algorithms, it is shown that with algorithm refinement linear parametric model-fitting can be extended to a wide range of complex data interpretation tasks, including time-frequency and time-scale analyses. A novel version of the IMP (incremental multiparameter) AML algorithm (using a partially deterministic and partially stochastic signal model) is suggested for adaptive detection, tracking and extraction from time-series waveforms of several modulated signal components of differing bandwidths.>