International audienceReconstructing a signal from its observations via a sensor device is usually called "deconvolution". Such reconstruction requires perfect knowledge of the impulse response of the sensor involved in the signal measurement. The lower this knowledge, the more biased the reconstruction. In this paper, we present a novel method for reconstructing a signal measured by a sensor whose impulse response is imprecisely known. This technique is based on modeling the relationship between the measurement and the signal via a concave capacity and extending the convolution concept to a concave set of impulse responses. The reconstructed signal is interval-valued, thus reflecting the poor knowledge of the sensor impulse response
A method for recovering a signal by measuring the signal to produce a plurality of compressive sensi...
A novel approach to the recognition of the signals degraded by a linear time-inwtriant system with a...
International audienceThe problem of signal deconvolution occurs in many appllcations, particularly ...
In the last 10 years, there has been increasing interest in interval valued data in signal processin...
AbstractIn most sensor measure based applications, the raw sensor signal has to be processed by an a...
International audienceIn most sensor measure based applications, the raw sensor signal has to be pro...
We present a novel solution to a 'hands-off' deconvolution problem in which the data to be deconvolv...
. The deconvolution problem is addressed in stages beginning with the interpolation problem when lit...
The recently introduced theory of Compressive Sensing (CS) enables a new method for signal recovery ...
Abstract: This paper demonstrates the effectiveness and versatility of an iterative deconvolution al...
The problem of determining the unknown responses of a system which is continuously excited by cyclos...
This paper presents an algorithm for reconstructing phase and magnitude responses of the impulse res...
This paper demonstrates the effectiveness and versatility of an iterative deconvolution algorithm in...
This paper demonstrates the effectiveness and versatility of an iterative deconvolution algorithm in...
Suppose that we have $r$ sensors and each one intends to send a function $z_i$ (e.g. a sign...
A method for recovering a signal by measuring the signal to produce a plurality of compressive sensi...
A novel approach to the recognition of the signals degraded by a linear time-inwtriant system with a...
International audienceThe problem of signal deconvolution occurs in many appllcations, particularly ...
In the last 10 years, there has been increasing interest in interval valued data in signal processin...
AbstractIn most sensor measure based applications, the raw sensor signal has to be processed by an a...
International audienceIn most sensor measure based applications, the raw sensor signal has to be pro...
We present a novel solution to a 'hands-off' deconvolution problem in which the data to be deconvolv...
. The deconvolution problem is addressed in stages beginning with the interpolation problem when lit...
The recently introduced theory of Compressive Sensing (CS) enables a new method for signal recovery ...
Abstract: This paper demonstrates the effectiveness and versatility of an iterative deconvolution al...
The problem of determining the unknown responses of a system which is continuously excited by cyclos...
This paper presents an algorithm for reconstructing phase and magnitude responses of the impulse res...
This paper demonstrates the effectiveness and versatility of an iterative deconvolution algorithm in...
This paper demonstrates the effectiveness and versatility of an iterative deconvolution algorithm in...
Suppose that we have $r$ sensors and each one intends to send a function $z_i$ (e.g. a sign...
A method for recovering a signal by measuring the signal to produce a plurality of compressive sensi...
A novel approach to the recognition of the signals degraded by a linear time-inwtriant system with a...
International audienceThe problem of signal deconvolution occurs in many appllcations, particularly ...