  cissa() is a MATLAB function for signal extraction by Circulant Singular
Spectrum Analysis, a procedure proposed in Bogalo et al (2021). cissa()
extracts the underlying signals in a time series identifying their frequency of
oscillation in an automated way, by just introducing the data and the window
length. This solution can be applied to stationary as well as to non-stationary
and non-linear time series. Additionally, in this paper, we solve some
technical issues regarding the beginning and end of sample data points. We also
introduce novel criteria in order to reconstruct the underlying signals
grouping some of the extracted components. The output of cissa() is the input
of the function group() to reconstruct the desired signals by further grouping
the extracted components. group() allows a novel user to create standard
signals by automated grouping options while an expert user can decide on the
number of groups and their composition. To illustrate its versatility and
performance in several fields we include 3 examples: an AM-FM synthetic signal,
an example of the physical world given by a voiced speech signal and an
economic time series. Possible applications include de-noising,
de-seasonalizing, de-trending and extracting business cycles, among others.
