Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Distributed Functional Scalar Quantization Simplified   Distributed functional scalar quantization (DFSQ) theory provides optimality
conditions and predicts performance of data acquisition systems in which a
computation on acquired data is desired. We address two limitations of previous
works: prohibitively expensive decoder design and a restriction to sources with
bounded distributions. We rigorously show that a much simpler decoder has
equivalent asymptotic performance as the conditional expectation estimator
previously explored, thus reducing decoder design complexity. The simpler
decoder has the feature of decoupled communication and computation blocks.
Moreover, we extend the DFSQ framework with the simpler decoder to acquire
sources with infinite-support distributions such as Gaussian or exponential
distributions. Finally, through simulation results we demonstrate that
performance at moderate coding rates is well predicted by the asymptotic
analysis, and we give new insight on the rate of convergence.

29
The categories of this paper are: funct-an
33
The categories of this paper are: plasm-ph
30
The categories of this paper are: q-alg
10
The categories of this paper are: q-bio
19
The categories of this paper are: eess
16
The categories of this paper are: stat
4
The categories of this paper are: cond-mat
14
The categories of this paper are: math-ph
28
The categories of this paper are: alg-geom
7
The categories of this paper are: hep-th
8
The categories of this paper are: hep-ex
6
The categories of this paper are: astro-ph
36
The categories of this paper are: cmp-lg
5
The categories of this paper are: gr-qc
26
The categories of this paper are: bayes-an
37
The categories of this paper are: supr-con