A Maximum A Posteriori Relaxation For Clustering The Labeled Stochastic Block Model

2021 ◽  
Author(s):  
Thomas Dittrich ◽  
Gerald Matz
Keyword(s):  
Maximum A Posteriori ◽  
A Posteriori ◽  
Block Model ◽  
Stochastic Block Model

Fast Algorithm on Stochastic Block Model for Exploring General Communities

2014 ◽  
Vol 24 (11) ◽  
pp. 2699-2709 ◽  
Author(s):  
Bian-Fang CHAI ◽  
Jian YU ◽  
Cai-Yan JIA ◽  
Jing-Hong WANG
Keyword(s):  
Fast Algorithm ◽  
Block Model ◽  
Stochastic Block Model

scholarly journals Threshold Computation for Spatially Coupled Turbo-Like Codes on the AWGN Channel

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 240
Author(s):  
Muhammad Umar Farooq ◽  
Alexandre Graell i Amat ◽  
Michael Lentmaier
Keyword(s):  
Gaussian Noise ◽  
Belief Propagation ◽  
Additive White Gaussian Noise ◽  
Maximum A Posteriori ◽  
Prediction Methods ◽  
Threshold Analysis ◽  
A Posteriori ◽  
Awgn Channel ◽  
Efficient Prediction ◽  
Binary Erasure Channel

In this paper, we perform a belief propagation (BP) decoding threshold analysis of spatially coupled (SC) turbo-like codes (TCs) (SC-TCs) on the additive white Gaussian noise (AWGN) channel. We review Monte-Carlo density evolution (MC-DE) and efficient prediction methods, which determine the BP thresholds of SC-TCs over the AWGN channel. We demonstrate that instead of performing time-consuming MC-DE computations, the BP threshold of SC-TCs over the AWGN channel can be predicted very efficiently from their binary erasure channel (BEC) thresholds. From threshold results, we conjecture that the similarity of MC-DE and predicted thresholds is related to the threshold saturation capability as well as capacity-approaching maximum a posteriori (MAP) performance of an SC-TC ensemble.

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