PROJECT TITLE :

Blind Deconvolution of Sparse Pulse Sequences Under a Minimum Distance Constraint: A Partially Collapsed Gibbs Sampler Method

ABSTRACT:

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–Gaussian prior modeling sparsity. In this paper, we extend this method by introducing a minimum distance constraint for the pulses in the sequence. This is physically relevant in applications including layer detection, medical imaging, seismology, and multipath parameter estimation. We propose a Bayesian method for blind deconvolution that is based on a modified Bernoulli–Gaussian prior including a minimum distance constraint factor. The core of our method is a partially collapsed Gibbs sampler (PCGS) that tolerates and even exploits the strong local dependencies introduced by the minimum distance constraint. Simulation results demonstrate significant performance gains compared to a recently proposed PCGS. The main advantages of the minimum distance constraint are a substantial reduction of computational complexity and of the number of spurious components in the deconvolution result.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE :On the Properties of the Rank-Two Null Space of Nonsparse and Canonical-Sparse Blind Deconvolution - 2018ABSTRACT:Blind deconvolution may be a ubiquitous nonlinear inverse downside in applications like wireless
PROJECT TITLE :Double Coupled Canonical Polyadic Decomposition for Joint Blind Source Separation - 2018ABSTRACT:Joint blind supply separation (J-BSS) is an rising knowledge-driven technique for multi-set information-fusion. In
PROJECT TITLE :Classification Based on Euclidean Distance Distribution for Blind Identification of Error Correcting Codes in Noncooperative Contexts - 2018ABSTRACT:The use of channel code is mandatory in current digital communication
PROJECT TITLE :Blind Stereoscopic Video Quality Assessment From Depth Perception to Overall Experience - 2018ABSTRACT:Stereoscopic video quality assessment (SVQA) may be a challenging drawback. It has not been well investigated
PROJECT TITLE :A Likelihood-Based Algorithm for Blind Identification of QAM and PSK Signals - 2018ABSTRACT:This Project presents a chance-based mostly methodology for automatically identifying totally different quadrature amplitude

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry