Adaptive MLSE receiver over rapidly fading channels
Signal Processing - Special issue on emerging techniques for communication terminals
Conditional mean and maximum likelihood approaches to multiharmonicfrequency estimation
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Two algorithms for adaptive retrieval of slowly time-varyingmultiple cisoids in noise
IEEE Transactions on Signal Processing
Estimation and tracking of complex-valued quasi-periodically varying systems
Automatica (Journal of IFAC)
New Algorithms for Adaptive Notch Smoothing
IEEE Transactions on Signal Processing
| Hi-index | 22.14 |
The problem of both causal and noncausal identification of linear stochastic systems with quasi-harmonically varying parameters is considered. The quasi-harmonic description allows one to model nonsinusoidal quasi-periodic parameter changes. The proposed identification algorithms are called generalized adaptive comb filters/smoothers because in the special signal case they reduce down to adaptive comb algorithms used to enhance or suppress nonstationary harmonic signals embedded in noise. The paper presents a thorough statistical analysis of generalized adaptive comb algorithms, and demonstrates their statistical efficiency in the case where the fundamental frequency of parameter changes varies slowly with time according to the integrated random-walk model.