An analysis on the applications of Markov random fields in error correcting codes of nano memory cells

This paper Compares various Error correcting codes in Nano scale Memory cells in terms of Belief Propagation Algorithm which is applied in a Markov Random Field (MRF). Soft error correction is critical for different Nano scale devices performing storage. As the Nano memories are with High fault rates, the conventional Error correcting Codes (ECCs) are not directly applicable. To achieve higher error correcting capability, a system is required that has high error detecting and correcting ability, with toleration to relatively high soft error rates. Also it requires sparse encoding, decoding and checker circuits, So that they can be synthesized using simple Nano scale hardware. In this paper the comparison is made using Belief Propagation Algorithm which is applied on Bipartite Graphs which are the MRFs.