Bayesian Deconvolution of Vessel Residence Time Distribution

Residence Time Distribution for Tubular Reactors

In the core of Chemical Engineering is the reactor design that includes most of all scientific disciplines. The reactor, in general, are treated ideally: mixed and plug-flow patterns. Unfortunately, it is observed in the real world a very different behavior from that expected. Thus, to characterize nonideal reactors is used, among others, residence time distribution function E(t), mean residenc...

Inferring the Distribution of Households' Duration of Residence from Data on Current Residence Time

Residence time distribution for a class of Gaussian Markov processes.

We study the distribution of residence time or equivalently that of "mean magnetization" for a family of Gaussian Markov processes indexed by a positive parameter alpha. The persistence exponent for these processes is simply given by theta=alpha but the residence time distribution is nontrivial. The shape of this distribution undergoes a qualitative change as theta increases, indicating a sharp...

Revisiting Bayesian blind deconvolution

Blind deconvolution involves the estimation of a sharp signal or image given only a blurry observation. Because this problem is fundamentally ill-posed, strong priors on both the sharp image and blur kernel are required to regularize the solution space. While this naturally leads to a standard MAP estimation framework, performance is compromised by unknown trade-off parameter settings, optimiza...

Bayesian Regularization and Nonnegative Deconvolution for Time Delay Estimation

Bayesian Regularization and Nonnegative Deconvolution (BRAND) is proposed for estimating time delays of acoustic signals in reverberant environments. Sparsity of the nonnegative filter coefficients is enforced using an L1-norm regularization. A probabilistic generative model is used to simultaneously estimate the regularization parameters and filter coefficients from the signal data. Iterative ...