Image deconvolution and reconstruction are inverse problems which are encountered in a
wide array of applications. Due to the ill-posedness of such problems, their resolution …

Biosignals have quite low signal-to-noise ratio and are often corrupted by different types of
artifacts and noises originated from both external and internal sources. The presence of …

In this paper, we introduce a variational Bayesian algorithm (VBA) for image blind
deconvolution. Our VBA generic framework incorporates smoothness priors on the unknown …

Abstract The Modal Composition Beamforming (MCB) method can quickly achieve the
localization of fast-rotating sound sources; however, its low resolution and unclear applied …

In this paper, a methodology is investigated for signal recovery in the presence of non-
Gaussian noise. In contrast with regularized minimization approaches often adopted in the …

Sparse Bayesian learning is a powerful framework for expressing compressed sensing
problems in the language of Bayesian inference, but its principal algorithm-the variational …

The noise distribution in the mechanical system is tightly connected to the structure design
and particular operating conditions. The noise source localization can effectively assist with …

It is valuable to improve the resolution and speed of acoustic beamforming in real-time
measurement, especially fault location, noise mapping, and so on. However, multiplication …

This paper considers the Bayesian filtering problem in high-dimensional nonlinear state-
space systems. In such systems, classical particle filters (PFs) are impractical due to the …

Sound source visualization has been widely used in many scenarios such as aerospace,
industrial production, and urban management. Sound source localization technology plays …