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A nonlinear prediction approach to the blind separation of convolutive mixtures
(SpringerNew YorkEUA, 2007)
Correlation-Based Amplitude Estimation of Coincident Partials in Monaural Musical Signals
(Hindawi Publishing CorporationNew YorkEUA, 2010)
Recovering Latent Signals from a Mixture of Measurements Using a Gaussian Process Prior
(IEEE, 2017)
In sensing applications, sensors cannot always mea-sure the latent quantity of interest at the required resolution, some-times they can only acquire a blurred version of it due the sensor’stransfer function. To recover ...
Vacancy state detector oriented to convolutional neural network, background subtraction and embedded systems
(Universidade Tecnológica Federal do ParanáPonta GrossaBrasilCiência da ComputaçãoUTFPR, 2019-12-11)
Much has been discussed recently related to population ascension, the reasons for this event, and in particular, the aspects of society affected. Over the years, the city governments realized a higher level of growth, ...
Spectral mixture kernels for Multi-Output Gaussian processes
(Universidad de Chile, 2017)
Multi-Output Gaussian Processes (MOGPs) are the multivariate extension of Gaussian processes (GPs \cite{Rasmussen:2006}), a Bayesian nonparametric method for univariate regression. MOGPs address the multi-channel regression ...
Almost sure and -convergence of the traces of Laguerre processes to the family of dilations of the standard free Poisson distribution are established. We also prove that the fl uctuations around the limiting proces s, converge weakly to a continuous centered Gaussian process. The almost sure convergence on compact time intervals of the largest and smallest eigenvalues processes is also established
(Centro de Investigación en Matemáticas AC, 2009)