Signal reconstruction by means of Embedding, Clustering and AutoEncoder Ensembles

We study the denoising and reconstruction of corrupted signals by means of AutoEncoder ensembles. In order to guarantee experts' diversity in the ensemble, we apply, prior to learning, a dimensional reduction pass (to map the examples into a suitable Euclidean space) and a partitional clustering pass: each cluster is then used to train a distinct AutoEncoder. We study the approach with an audio file benchmark: the original signals are artificially corrupted by Doppler effect and reverb. The results support the comparative effectiveness of the approach, w.r.t. the approach based on a single AutoEncoder. The processing pipeline using Local Linear Embedding, k means, then k Convolutional Denoising AutoEncoders reduces the reconstruction error by 35% w.r.t. the baseline approach

Two-fermion relativistic bound states in Light-Front Dynamics

In the Light-Front Dynamics, the wave function equations and their numerical solutions, for two fermion bound systems, are presented. Analytical expressions for the ladder one-boson exchange interaction kernels corresponding to scalar, pseudoscalar, pseudovector and vector exchanges are given. Different couplings are analyzed separately and each of them is found to exhibit special features. The results are compared with the non relativistic solutions.Comment: 40 pages, to be published in Phys. Rev. C, .tar.gz fil

From samples to populations in retinex models

Some spatial color algorithms, such as Brownian Milano retinex (MI-retinex) and random spray retinex (RSR), are based on sampling. In Brownian MI-retinex, memoryless random walks (MRWs) explore the neighborhood of a pixel and are then used to compute its output. Considering the relative redundancy and inefficiency of MRW exploration, the algorithm RSR replaced the walks by samples of points (the sprays). Recent works point to the fact that a mapping from the sampling formulation to the probabilistic formulation of the corresponding sampling process can offer useful insights into the models, at the same time featuring intrinsically noise-free outputs. The paper continues the development of this concept and shows that the population-based versions of RSR and Brownian MI-retinex can be used to obtain analytical expressions for the outputs of some test images. The comparison of the two analytic expressions from RSR and from Brownian MI-retinex demonstrates not only that the two outputs are, in general, different but also that they depend, in a qualitatively different way, upon the features of the image

Improving probabilistic flooding using topological indexes

Unstructured networks are characterized by constrained resources and require protocols that efficiently utilize bandwidth and battery power. Probabilistic flooding, allows nodes to rebroadcast RREQ packets with some probability p, thus reducing the overhead. The key issue in of this algorithm consists of determining p. The techniques proposed so far either use a fixed p determined by a priori considerations, or a p variable from one node to the other - set, for instance based on node degree or distance between source and destination - or even a dynamic p based on the number of redundant messages received by the nodes. In order to make the computation of forwarding probability p works optimally regardless of changing of topology, we propose to set p based on the node role within the message dissemination process. Specifically, we propose to identify such role based on the nodes' clustering coefficients (the lower the coefficient, the higher the forwarding probability). The performance of the algorithm is evaluated in terms of routing overhead, packet delivery ratio, and end-to-end delay. The algorithm pays a price in terms of computation time for discovering the clustering coefficient, however reduces unnecessary and redundant control messages and achieves a significant improvements in both dense and sparse networks in terms of packet delivery ratio. We compare by simulation the performance of this algorithm with the one of the most representative competing algorithms

Photodisintegration of the triton with realistic potentials

The process $\gamma + t \to n + d$ is treated by means of three-body integral equations employing in their kernel the W-Matrix representation of the subsystem amplitudes. As compared to the plane wave (Born) approximation the full solution of the integral equations, which takes into account the final state interaction, shows at low energies a 24% enhancement. The calculations are based on the semirealistic Malfliet-Tjon and the realistic Paris and Bonn B potentials. For comparison with earlier calculations we also present results for the Yamaguchi potential. In the low-energy region a remarkable potential dependence is observed, which vanishes at higher energies.Comment: 16 pages REVTeX, 8 postscript figures included, uses epsfig.st

Dalitz plot analysis of D_s+ and D+ decay to pi+pi-pi+ using the K-matrix formalism

FOCUS results from Dalitz plot analysis of D_s+ and D+ to pi+pi-pi+ are presented. The K-matrix formalism is applied to charm decays for the first time to fully exploit the already existing knowledge coming from the light-meson spectroscopy experiments. In particular all the measured dynamics of the S-wave pipi scattering, characterized by broad/overlapping resonances and large non-resonant background, can be properly included. This paper studies the extent to which the K-matrix approach is able to reproduce the observed Dalitz plot and thus help us to understand the underlying dynamics. The results are discussed, along with their possible implications on the controversial nature of the sigma meson.Comment: To be submitted to Phys.Lett.B A misprint corrected in formula