Name
Title | ||
|---|---|---|
Edgeworth series expansion of the conditional mean and the optimality of non-linear Volterra filters |
Abstract | ||
|---|---|---|
The authors address the problem of the optimality of the Volterra filters, in comparison with the optimal estimator in a minimum mean square error sense: the conditional mean. Notation and definition concerning cumulants, moments, generalized cumulants and Hermite tensors are introduced. The best Volterra estimation of a random variable x from a random observation vector Y is calculated, and an Edgeworth series expansion of the conditional mean, the optimal estimator, is given. In the case of a Gaussian observation vector, it is shown that the Volterra estimator and the expansion of the conditional mean are equal, providing a result concerning the optimality of Volterra filters |
Year | DOI | Venue |
|---|---|---|
1992 | 10.1109/ICASSP.1992.226579 | Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference |
Keywords | DocType | Volume |
estimation theory,filtering and prediction theory,signal processing,statistical analysis,tensors,edgeworth series expansion,gaussian observation vector,hermite tensors,volterra filters,conditional mean,cumulants,minimum mean square error,moments,nonlinear filters,optimal estimator,optimality,random observation vector,random variable,series expansion,random variables,optimal estimation,gaussian processes,vectors,probability density function,tensile stress,cumulant,bayesian methods | Conference | 5 |
ISSN | Citations | PageRank |
1520-6149 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amblard, P.-O. | 1 | 53 | 6.30 |
| Baudois, D. | 2 | 0 | 0.68 |
| Jean-Louis Lacoume | 3 | 62 | 12.13 |