Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Walsh Sampling with Incomplete Noisy Signals   With the advent of massive data outputs at a regular rate, admittedly, signal
processing technology plays an increasingly key role. Nowadays, signals are not
merely restricted to physical sources, they have been extended to digital
sources as well.
  Under the general assumption of discrete statistical signal sources, we
propose a practical problem of sampling incomplete noisy signals for which we
do not know a priori and the sampling size is bounded. We approach this
sampling problem by Shannon's channel coding theorem. Our main results
demonstrate that it is the large Walsh coefficient(s) that characterize(s)
discrete statistical signals, regardless of the signal sources. By the
connection of Shannon's theorem, we establish the necessary and sufficient
condition for our generic sampling problem for the first time. Our generic
sampling results find practical and powerful applications in not only
statistical cryptanalysis, but software system performance optimization.

9
The categories of this paper are: nlin
32
The categories of this paper are: atom-ph
16
The categories of this paper are: stat
13
The categories of this paper are: quant-ph
5
The categories of this paper are: gr-qc
35
The categories of this paper are: mtrl-th
23
The categories of this paper are: solv-int
29
The categories of this paper are: funct-an
11
The categories of this paper are: hep-lat
14
The categories of this paper are: math-ph
27
The categories of this paper are: comp-gas
19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
4
The categories of this paper are: cond-mat
28
The categories of this paper are: alg-geom
36
The categories of this paper are: cmp-lg