Dec 25, 2008 · We perform approximate Bayesian inference using belief propagation (BP) decoding, which represents the CS encoding matrix as a graphical model.

Jun 24, 2009 · We perform approximate Bayesian inference using belief propagation (BP) decoding, which represents the CS encoding matrix as a graphical model.

In this paper, we develop a sparse encoder matrix and a belief propagation (BP) decoder to accelerate CS encoding and decoding under the Bayesian framework. We ...

Dec 25, 2008 · We perform approximate Bayesian infer- ence using belief propagation (BP) decoding, which represents the CS encoding matrix as a graphical model ...

This work performs asymptotically optimal Bayesian inference using belief propagation (BP) decoding, which represents the CS encoding matrix as a graphical ...

Compressed sensing is an emerging field that enables to reconstruct sparse or com- pressible signals from a small number of linear projections. We describe a ...

We perform asymptotically optimal Bayesian inference using belief propagation (BP) decoding, which represents the CS encoding matrix as a graphical model. Fast ...

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This webpage describes the Matlab files used to simulate our CS-BP algorithm: compressive sensing decoding via belief propagation. Technical details appear in ...

To this end, a CS scheme based on Belief Propagation (BP) algorithm is proposed to compress correlated sparse (compressible) signals in this paper. The BP ...