Jump-Penalized Least Absolute Values Estimation of Scalar or Circle-Valued Signals
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Recently, we proposed a noniterative cepstral technique for exact signal recovery in frequency-domain optical-coherence tomography. In this paper, we address the influence of measurement noise on the performance of the method. We derive analytical expressi ...
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We consider the problem of optimizing the parameters of a given denoising algorithm for restoration of a signal corrupted by white Gaussian noise. To achieve this, we propose to minimize Stein's unbiased risk estimate (SURE) which provides a means of asses ...
In this paper, we introduce the notion of a constrained Minkowski sum: for two (finite) point-sets P, Q subset of R-2 and a set of k inequalities Ax >= b, it is defined as the point-set (P circle plus Q)(Ax >= b) = {x = p + q vertical bar p is an element o ...
Disorientation induced by G-forces during aerobatic flight generates difficulties for the pilots to perfectly align their aerobatic maneuver. This paper presents a modular wearable system for enhancing training of aerobatic pilots. A combination of acceler ...
We consider the problem of ranging with Impulse Radio (IR) Ultra-WideBand (UWB) radio under weak Line Of Sight (LOS) environments and additive Gaussian noise. We use a Bayesian approach where the prior distribution of the channel follows the IEEE 802.15.4a ...
This thesis focuses on the decisional process of autonomous systems, and more particularly, on the way to take a decision when the time at disposal in order to assess the whole situation is shorter than necessary. Indeed, numerous systems propose solutions ...
Conventional sampling (Shannon's sampling formulation and its approximation-theoretic counterparts) and interpolation theories provide effective solutions to the problem of reconstructing a signal from its samples, but they are primarily restricted to the ...
Generalized Linear Models have become a commonly used tool of data analysis. Such models are used to fit regressions for univariate responses with normal, gamma, binomial or Poisson distribution. Maximum likelihood is generally applied as fitting method. I ...
Diffusion LMS is a distributed algorithm that allows a network of nodes to solve estimation problems in a fully distributed manner by relying solely on local interactions. The algorithm consists of two steps: a consultation step whereby each node combines ...
We propose a novel algorithm for denoising Poisson-corrupted images, that performs a signal-adaptive thresholding of the undecimated Haar wavelet coefficients. A Poisson's unbiased MSE estimate is devised and adapted to arbitrary transform-domain pointwis ...