An upper bound is obtained for the restoration error variance of a sample restoration method for autoregressive processes that was presented by A.J.E.M. Janssen et al. (ibid., vol.ASSP-34, p.317-30, Apr. 1986). The upper bound derived is lower if the autoregressive process has poles close to the unit circle of the complex plane. This situation corresponds to a peaky signal spectrum. The bound is valid for the case in which one sample is unknown in a realization of an autoregressive process of arbitrary finite orde
We evaluate the performance of a feature-preserving filtering algorithm over a range of images corru...
In the framework of speech enhancement, several parametric approaches based on an a priori model for...
In the framework of speech enhancement, several parametric approaches based on an a priori model for...
An upper bound is obtained for the restoration error variance of a sample restoration method for aut...
This paper presents an adaptive algorithm for the restoration of lost sample values in discrete-time...
Algorithms for the restoration of unknown samples at known positions embedded in a neighborhood of k...
Algorithms for the restoration of unknown samples at known positions embedded in a neighborhood of k...
This paper presents an adaptive algorithm for the restoration of lost sample values in discrete-time...
The authors present an adaptive algorithm for the restoration of lost sample values in discrete-time...
The authors present an adaptive algorithm for the restoration of lost sample values in discrete-time...
The authors present an adaptive algorithm for the restoration of lost sample values in discrete-time...
The authors present an adaptive algorithm for the restoration of lost sample values in discrete-time...
Assuming that the errors of an autoregressive process form a sequence of martingale differences, the...
A univariate autoregressive process of order p with deterministic mean function and a root close to ...
Abstract. We consider an non-symmetric half plane autoregressive image, where the image intensity of...
We evaluate the performance of a feature-preserving filtering algorithm over a range of images corru...
In the framework of speech enhancement, several parametric approaches based on an a priori model for...
In the framework of speech enhancement, several parametric approaches based on an a priori model for...
An upper bound is obtained for the restoration error variance of a sample restoration method for aut...
This paper presents an adaptive algorithm for the restoration of lost sample values in discrete-time...
Algorithms for the restoration of unknown samples at known positions embedded in a neighborhood of k...
Algorithms for the restoration of unknown samples at known positions embedded in a neighborhood of k...
This paper presents an adaptive algorithm for the restoration of lost sample values in discrete-time...
The authors present an adaptive algorithm for the restoration of lost sample values in discrete-time...
The authors present an adaptive algorithm for the restoration of lost sample values in discrete-time...
The authors present an adaptive algorithm for the restoration of lost sample values in discrete-time...
The authors present an adaptive algorithm for the restoration of lost sample values in discrete-time...
Assuming that the errors of an autoregressive process form a sequence of martingale differences, the...
A univariate autoregressive process of order p with deterministic mean function and a root close to ...
Abstract. We consider an non-symmetric half plane autoregressive image, where the image intensity of...
We evaluate the performance of a feature-preserving filtering algorithm over a range of images corru...
In the framework of speech enhancement, several parametric approaches based on an a priori model for...
In the framework of speech enhancement, several parametric approaches based on an a priori model for...