The advantage of using the matching statistics is that it is not based on fixed-length subwords, but it can capture also variable length matches, in contrast to most methods that are based on fixed sets of k-mers.
Learning models for wavelet coefficients have been mainly based on fixed-length sequences, but real applications often require to model variable-length, very long or real-time sequences.
Alternative approaches based on fixed-length sequences and receive strategies with a lower complexity are presented in our prior work [24, 25].
In this paper, by taking full advantage of local Voronoi neighbor structures (VNSs), e.g. local structural stability and distortion insensitivity, we propose an alignment-free bio-cryptosystem based on fixed-length bit-string representations extracted from modified VNSs, which are rotation- and translation-invariant and distortion robust.
As opposed to the above audio identification algorithms based on fixed-length framing plus heavy overlap, which are usually more or less susceptible to time variations, Bardeli and Kurth proposed in [21] to divide audio signals into unequal-length disjoint time intervals.
At low level taxa, trees based on fixed-length k-mers and maximal k-mers are consistent, as they both correctly group together Eukaryotes, Proteobacteria, Euryarcheota and Crenarchaeota.
The recent approaches, which addressed full periodicity, partial periodicity, perfect and imperfect periodicity [7], and asynchronous periodicity [18] are all based on fixed size and adjacent time units and fixed length of discovered patterns.
Exploratory analyses based on fixed effects models were also conducted.
