Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Independent Component Analysis Over Galois Fields   We consider the framework of Independent Component Analysis (ICA) for the
case where the independent sources and their linear mixtures all reside in a
Galois field of prime order P. Similarities and differences from the classical
ICA framework (over the Real field) are explored. We show that a necessary and
sufficient identifiability condition is that none of the sources should have a
Uniform distribution. We also show that pairwise independence of the mixtures
implies their full mutual independence (namely a non-mixing condition) in the
binary (P=2) and ternary (P=3) cases, but not necessarily in higher order (P>3)
cases. We propose two different iterative separation (or identification)
algorithms: One is based on sequential identification of the smallest-entropy
linear combinations of the mixtures, and is shown to be equivariant with
respect to the mixing matrix; The other is based on sequential minimization of
the pairwise mutual information measures. We provide some basic performance
analysis for the binary (P=2) case, supplemented by simulation results for
higher orders, demonstrating advantages and disadvantages of the proposed
separation approaches.

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The categories of this paper are: funct-an
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The categories of this paper are: patt-sol
16
The categories of this paper are: stat
24
The categories of this paper are: dg-ga
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The categories of this paper are: mtrl-th
20
The categories of this paper are: acc-phys
32
The categories of this paper are: atom-ph
15
The categories of this paper are: nucl-ex
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The categories of this paper are: adap-org
10
The categories of this paper are: q-bio
33
The categories of this paper are: plasm-ph
4
The categories of this paper are: cond-mat
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The categories of this paper are: chao-dyn
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The categories of this paper are: hep-lat
18
The categories of this paper are: econ
34
The categories of this paper are: chem-ph