Name
Abstract | ||
|---|---|---|
We present a new estimator of the entropy of continuous signals. We model the unknown probability density of data in the form of an AR spectrum density and use regularized long-AR models to identify the AR parameters. We then derive both an analytical expression and a practical procedure for estimating the entropy from sample data. We indicate how to incorporate recursive and adaptive features in the procedure. We evaluate and compare the new estimator with other estimators based on histograms, kernel density models, and order statistics. Finally, we give several examples of applications. An adaptive version of our entropy estimator is applied to detection of law changes, blind deconvolution, and source separation |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1109/78.845926 | IEEE Transactions on Signal Processing |
Keywords | Field | DocType |
adaptive estimation,adaptive signal detection,adaptive signal processing,autoregressive processes,blind equalisers,deconvolution,entropy,probability,spectral analysis,statistical analysis,ar parameters identification,ar spectrum density,adaptive entropy estimator,blind deconvolution,blind equalization,continuous signals,histograms,kernel density models,order statistics,probability density,recursive estimator,regularized long-ar models,sample data,signal detection,signal entropy estimation,signal processing,source separation,indexing terms,spectrum analysis,kernel density,probability density function,spectrum,kernel,order statistic,entropy estimation,ar model,change blindness | Blind deconvolution,Minimax estimator,Binary entropy function,Artificial intelligence,Adaptive filter,Order statistic,Kernel density estimation,Mathematical optimization,Pattern recognition,Algorithm,Principle of maximum entropy,Mathematics,Estimator | Conference |
Volume | Issue | ISSN |
48 | 6 | 1053-587X |
Citations | PageRank | References |
33 | 4.25 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bercher, J.-F. | 1 | 59 | 8.53 |
| Vignat, C. | 2 | 33 | 4.25 |