Consistent Estimation of Continuous-Time Signals from Nonlinear Transformations of Noisy Samples,
Abstract
In general, a signal cannot be reconstructed from its sign, i.e., from its hard limited version. However, by deliberately adding noise to samples of the signal prior to hard limiting, it is shown that the signals can be estimated consistently from its hard limited noisy samples as the sampling rate tends to infinity. In fact, such estimates are shown to converge with probability one to the signal and also, to be asymptotically normal. The estimates, which are generally nonlinear, can be made linear by a proper choice of the noise distribution. These rather unexpected results hold for all bounded and uniformly continuous signals. In addition to the hard limiter, such results are also established for certain monotonic and non-monotonic non-linearities. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 10, 1980
- Accession Number
- ADA082239
Entities
People
- Elias Masry
- S. Cambanis
Organizations
- University of California, San Diego