Window-based estimates for stochastic harmonic regression models are
useful for cases where 
harmonic parameters appear to be time-varying. 
Least squares
estimates for harmonic models with one fundamental 
have been studied and asymptotic variance 
expressions have been developed. 
This paper extends these results to weighted least squares for 
the multiple fundamental case, and presents an application in signal
processing.