The two source maximum likelihood function
John E. Piper
Abstract
John E. Piper
Abstract
The maximum likelihood method is designed to yield high resolution estimates in a multiple source environment. The article derive a simplified representation of the maximum likelihood function for the two source case. This case is instructive to understand when and why the full power of the maximum likelihood method should be used. This approach extends the results of a previous paper (see J. Piper, IEEE Trans. Signal Processing, vol.42, no.2, p.412, 1994) that showed how the maximum likelihood function calculation can be transformed from a matrix problem to a vector product. The maximum likelihood function for spectral estimation is given.>
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The maximum likelihood method is designed to yield high resolution estimates in a multiple source environment. The article derive a simplified representation of the maximum likelihood function for the two source case. This case is instructive to understand when and why the full power of the maximum likelihood method should be used. This approach extends the results of a previous paper (see J. Piper, IEEE Trans. Signal Processing, vol.42, no.2, p.412, 1994) that showed how the maximum likelihood function calculation can be transformed from a matrix problem to a vector product. The maximum likelihood function for spectral estimation is given.>
Key concepts: Maximum likelihood, Computer science, Likelihood function, Function (biology), Maximum likelihood sequence estimation, Algorithm, Mathematics, Estimation theory