Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Novel LDPC Decoder via MLP Neural Networks   In this paper, a new method for decoding Low Density Parity Check (LDPC)
codes, based on Multi-Layer Perceptron (MLP) neural networks is proposed. Due
to the fact that in neural networks all procedures are processed in parallel,
this method can be considered as a viable alternative to Message Passing
Algorithm (MPA), with high computational complexity. Our proposed algorithm
runs with soft criterion and concurrently does not use probabilistic quantities
to decide what the estimated codeword is. Although the neural decoder
performance is close to the error performance of Sum Product Algorithm (SPA),
it is comparatively less complex. Therefore, the proposed decoder emerges as a
new infrastructure for decoding LDPC codes.

16
The categories of this paper are: stat
10
The categories of this paper are: q-bio
12
The categories of this paper are: nucl-th
32
The categories of this paper are: atom-ph
7
The categories of this paper are: hep-th
3
The categories of this paper are: physics
17
The categories of this paper are: q-fin
30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
6
The categories of this paper are: astro-ph
34
The categories of this paper are: chem-ph
35
The categories of this paper are: mtrl-th
26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph
28
The categories of this paper are: alg-geom
36
The categories of this paper are: cmp-lg