Generalized Smoothing Splines and the Optimal Discretization of the Wiener Filter
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The chapter describes recent developments in distributed processing over adaptive networks. The resulting adaptive learning rules rely on local data at the individual nodes and on collaborations among neighboring nodes in order to exploit the space-time di ...
We present an unscented Kalman filter to identify the phase step imparted to a piezoelectric transducer in phase shifting interferometry in the presence of Gaussian noise. The advantage of the proposed algorithm lies in its ability to determine the phase s ...
Efficient and reliable spectrum sensing plays a critical role in cognitive radio networks. This paper presents a cooperative sequential detection scheme to reduce the average sensing time that is required to reach a detection decision. In the scheme, each ...
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 ...
This paper is concerned with input adaptation in dynamic processes in order to guarantee feasible and optimal operation despite the presence of uncertainty. For optimal control problems having terminal constraints, two sets of directions can be distinguish ...
This paper presents three recursive Bayesian filtering approaches in phase shifting interferometry involving a piezoelectric device (PZT). The three approaches are extended Kalman filtering, unscented Kalman filtering, and particle filtering. These approac ...
This paper investigates to which extent the tails of left and right binaural room impulse responses (BRIRs) can be replaced by white Gaussian noise that has been processed to have the same energy decay relief and interaural coherence as the original BRIRs’ ...
In the field of image segmentation, most level-set-based active-contour approaches take advantage of a discrete representation of the associated implicit function. We present in this paper a different formulation where the implicit function is modeled as a ...
Non-local means (NLM) provides a powerful framework for denoising. However, there are a few parameters of the algorithm-most notably, the width of the smoothing kernel-that are data-dependent and difficult to tune. Here, we propose to use Stein's unbiased ...
Institute of Electrical and Electronics Engineers2009
This paper proposes a new approach for the analysis of reconstructed interference fields in digital holographic interferometry. In the proposed approach the interference phase to be estimated is conceived as a piecewise polynomial signal; consequently, eac ...