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Method and system for linear processing of an input using Gaussian belief propagation

Dolev Danny, HUJI, School of Computer Science and Engineering, CS - Machine Learning

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Methods and systems for processing an input. An input vector y is received that represents a noisy observation of Ax, where A is a data matrix and x is a data vector of unknown variables. Data vector x is recovered from the received input vector y via an iterative method. The recovering comprises determining an inference of a vector of marginal means over a graph G, where the graph G is of a joint Gaussian probability density function p(x) associated with noise in the received input vector y.

 

Granted US Patent: 8,139,656

Patent Status

Granted US 8,139,656

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