Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Algebraic Optimization of Binary Spatially Coupled Measurement Matrices
  for Interval Passing   We consider binary spatially coupled (SC) low density measurement matrices
for low complexity reconstruction of sparse signals via the interval passing
algorithm (IPA). The IPA is known to fail due to the presence of harmful
sub-structures in the Tanner graph of a binary sparse measurement matrix, so
called termatiko sets. In this work we construct array-based (AB) SC sparse
measurement matrices via algebraic lifts of graphs, such that the number of
termatiko sets in the Tanner graph is minimized. To this end, we show for the
column-weight-three case that the most critical termatiko sets can be removed
by eliminating all length-12 cycles associated with the Tanner graph, via
algebraic lifting. As a consequence, IPA-based reconstruction with SC
measurement matrices is able to provide an almost error free reconstruction for
significantly denser signal vectors compared to uncoupled AB LDPC measurement
matrices.

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The categories of this paper are: cond-mat
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The categories of this paper are: hep-ph
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The categories of this paper are: stat
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The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
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The categories of this paper are: bayes-an
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The categories of this paper are: acc-phys
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The categories of this paper are: cmp-lg
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The categories of this paper are: dg-ga
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The categories of this paper are: q-fin
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The categories of this paper are: quant-ph
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The categories of this paper are: chem-ph
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The categories of this paper are: hep-ex
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The categories of this paper are: patt-sol
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The categories of this paper are: atom-ph
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The categories of this paper are: nucl-th