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Estimation of Hidden Frequencies for 2 D Stationary Processes
| Content Provider | Semantic Scholar |
|---|---|
| Author | Zhang, Hao |
| Copyright Year | 2001 |
| Abstract | We study a stationary random ®eld model that is composed of a signal of an unknown number of sine and cosine functions, and a coloured noise. This model has been used in image analysis and modelling spatial data, and is useful for signal extraction in the presence of coloured noise. The problem is to estimate the number of unknown frequencies and the unknown frequencies. The analogous time series model and related problems have been extensively studied. Our approach is based on some analytic properties of periodograms of stationary random ®elds that we establish in the paper. In particular, we show that the periodogram of a stationary random ®eld of a moving average has a uniform upper bound of O (ln(N)) where N 2 is the sample size, and that the periodogram of the observed process has a magnitude of the order N 2 uniformly in a neighbourhood of any hidden frequency, and much smaller outside. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.stat.purdue.edu/~zhanghao/Paper/twod.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | ARID1A wt Allele Image analysis Short Interspersed Nucleotide Elements Spectral density estimation Stationary process Time series |
| Content Type | Text |
| Resource Type | Article |
