Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Direct Signal Separation Via Extraction of Local Frequencies with
  Adaptive Time-Varying Parameters   In nature, real-world phenomena that can be formulated as signals (or in
terms of time series) are often affected by a number of factors and appear as
multi-component modes. The natural approach to understand and process such
phenomena is to decompose, or even better, to separate the multi-component
signals to their basic building blocks (called sub-signals or time-series
components, or fundamental modes). Recently the synchro-squeezing transform
(SST) and its variants have been developed for nonstationary signal separation.
More recently, a direct method of the time-frequency approach, called signal
separation operation (SSO), was introduced for multi-component signal
separation. While both SST and SSO are mathematically rigorous on the
instantaneous frequency (IF) estimation, SSO avoids the second step of the
two-step SST method in signal separation, which depends heavily on the accuracy
of the estimated IFs. In the present paper, we solve the signal separation
problem by constructing an adaptive signal separation operator (ASSO) for more
effective separation of the blind-source multi-component signal, via
introducing a time-varying parameter that adapts to local IFs. A recovery
scheme is also proposed to extract the signal components one by one, and the
time-varying parameter is updated for each component. The proposed method is
suitable for engineering implementation, being capable of separating
complicated signals into their sub-signals and reconstructing the signal trend
directly. Numerical experiments on synthetic and real-world signals are
presented to demonstrate our improvement over the previous attempts.

29
The categories of this paper are: funct-an
34
The categories of this paper are: chem-ph
22
The categories of this paper are: chao-dyn
3
The categories of this paper are: physics
26
The categories of this paper are: bayes-an
4
The categories of this paper are: cond-mat
1
The categories of this paper are: cs
13
The categories of this paper are: quant-ph
7
The categories of this paper are: hep-th
10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph
0
The categories of this paper are: hep-ph
35
The categories of this paper are: mtrl-th
36
The categories of this paper are: cmp-lg
6
The categories of this paper are: astro-ph
27
The categories of this paper are: comp-gas