THE ESTIMATION OF A SYSTEM PULSE TRANSFER FUNCTION IN THE PRESENCE OF NOISE,
Abstract
Efficient determination of system perameters from records of input-output data is important in many applications such as adaptive systems, process control, and communication over time-varying channels. Statistical estimation theory is applied to derive effective techniques for measurement of the pulse transfer function of a linear system from normal operating records obscured by additive noise. It is shown that the problem is equivalent to that of fitting a hyperplane to a set of observed points with random errors in certain coordinates. The methods of T. Koopmans are applied to obtain generalized least-squares estimates which are also maximum likelihood estimates when the noise is white and Gaussian.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 09, 1962
- Accession Number
- AD0282043
Entities
People
- Morris J. Levin
Organizations
- Massachusetts Institute of Technology