Bayesian Regularization and Nonnegative Deconvolution for Time Delay Estimation
نویسندگان
چکیده
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 update rules are derived under a Bayesian framework using the Expectation-Maximization procedure. The resulting time delay estimation algorithm is demonstrated on noisy acoustic data.
منابع مشابه
PSO-Optimized Blind Image Deconvolution for Improved Detectability in Poor Visual Conditions
Abstract: Image restoration is a critical step in many vision applications. Due to the poor quality of Passive Millimeter Wave (PMMW) images, especially in marine and underwater environment, developing strong algorithms for the restoration of these images is of primary importance. In addition, little information about image degradation process, which is referred to as Point Spread Function (PSF...
متن کاملExtended Mumford-Shah Regularization in Bayesian Estimation for Blind Image Deconvolution and Segmentation
We present an extended Mumford-Shah regularization for blind image deconvolution and segmentation in the context of Bayesian estimation for blurred, noisy images or video sequences. The MumfordShah functional is extended to have cost terms for the estimation of blur kernels via a newly introduced prior solution space. This functional is minimized using Γ -convergence approximation in an embedde...
متن کاملRegularization, maximum entropy and probabilistic methods in mass spectrometry data processing problems
This paper is a synthetic overview of regularization, maximum entropy and probabilistic methods for some inverse problems such as deconvolution and Fourier synthesis problems which arise in mass spectrometry. First we present a unified description of such problems and discuss the reasons why simple naı̈ve methods cannot give satisfactory results. Then we briefly present the main classical determ...
متن کاملMultipath Time-Delay Detection and Estimation - Signal Processing, IEEE Transactions on
A transmitted and known signal is observed at the receiver through more than one path in additive noise. The problem is to estimate the number of paths and, for each of them, the associated attenuation and delay. We propose a deconvolution approach with an additive regularization term built around an `1 norm. The underlying optimization problem is transformed into a quadratic program and is, th...
متن کاملBayesian Blind Deconvolution Using a Student-t Prior Model and Variational Bayesian Approximation
Deconvolution consists in estimating the input of a linear and invariant system from its output knowing its Impulse Response Function (IRF). When the IRF of the system is unknown, we are face to Blind Deconvolution. This inverse problem is ill-posed and needs prior information to obtain a satisfactory solution. Regularization theory, well known for simple deconvolution, is no more enough to obt...
متن کامل