Formulated as a least square problem under an l 0 constraint, sparse signal restoration is a
discrete optimization problem, known to be NP complete. Classical algorithms include, by …

地震数据子波提取, 是地震资料反褶积处理, 波阻抗反演以及正演模拟的基础工作.
准确的地震子波估计技术对于高分辨率, 高信噪比, 高保真度的地震勘探数据处理具有极为重要 …

Finite-difference time-domain forward modeling of ground-penetrating radar (GPR) is
becoming regularly used in model-based interpretation methods, such as full-waveform …

A new algorithm for simultaneous wavelet estimation and deconvolution of seismic reflection
signals is given. To remove the inherent ambiguity in this blind deconvolution problem, we …

Abstract Markov chain Monte Carlo (MCMC) methods, while facilitating the solution of many
complex problems in Bayesian inference, are not currently well adapted to the problem of …

This paper presents a hierarchical Bayesian model to reconstruct sparse images when the
observations are obtained from linear transformations and corrupted by an additive white …

We propose a new framework to extract the activity-related component in the BOLD
functional magnetic resonance imaging (fMRI) signal. As opposed to traditional fMRI signal …

This short book is for students, professors and professionals interested in signal processing
of seismic data using MATLAB (TM). The step-by-step demo of the full reflection seismic data …

For blind deconvolution of an unknown sparse sequence convolved with an unknown pulse,
a powerful Bayesian method employs the Gibbs sampler in combination with a Bernoulli …

Analysis of functional magnetic resonance imaging (fMRI) data focuses essentially on two
questions: first, a detection problem that studies which parts of the brain are activated by a …