Discovering frequent serial episodes in symbolic sequences for rainfall dataset

2012 ◽  
Author(s):  
AlMahdi Ahmed ◽  
Azuraliza Abu Bakar ◽  
Abdul Razak Hamdan ◽  
Sharifah Mastura Syed Abdullah ◽  
Othman Jaafar
Keyword(s):  
Symbolic Sequences ◽  
Serial Episodes

scholarly journals Memory order decomposition of symbolic sequences

2021 ◽  
Vol 104 (1) ◽  
Author(s):  
Unai Alvarez-Rodriguez ◽  
Vito Latora
Keyword(s):  
Symbolic Sequences

Cyclic Reduction of Symbolic Sequences

2019 ◽  
pp. 103-114
Author(s):  
Marlos A. G. Viana ◽  
Vasudevan Lakshminarayanan
Keyword(s):  
Cyclic Reduction ◽  
Symbolic Sequences

scholarly journals Physical complexity of symbolic sequences

2000 ◽  
Vol 137 (1-2) ◽  
pp. 62-69 ◽  
Author(s):  
C. Adami ◽  
N.J. Cerf
Keyword(s):  
Symbolic Sequences ◽  
Physical Complexity

Equivalence of the Markov chains and two-sided symbolic sequences

2006 ◽  
Vol 76 (6) ◽  
pp. 1015-1021 ◽  
Author(s):  
S. S Apostolov ◽  
Z. A Mayzelis ◽  
O. V Usatenko ◽  
V. A Yampol'skii
Keyword(s):  
Markov Chains ◽  
Symbolic Sequences

Kernel Generative Topographic Mapping of Protein Sequences

2012 ◽  
pp. 195-208
Author(s):  
M.I. Cardenas ◽  
A. Vellido ◽  
I. Olier ◽  
X. Rovira ◽  
J. Giraldo
Keyword(s):  
Data Analysis ◽  
Kernel Method ◽  
Protein Sequences ◽  
Topographic Mapping ◽  
Complex Data ◽  
Generative Topographic Mapping ◽  
Protein Amino Acid ◽  
Genomics And Proteomics ◽  
The World ◽  
Symbolic Sequences

The world of pharmacology is becoming increasingly dependent on the advances in the fields of genomics and proteomics. The –omics sciences bring about the challenge of how to deal with the large amounts of complex data they generate from an intelligence data analysis perspective. In this chapter, the authors focus on the analysis of a specific type of proteins, the G protein-couple receptors, which are the target for over 15% of current drugs. They describe a kernel method of the manifold learning family for the analysis of protein amino acid symbolic sequences. This method sheds light on the structure of protein subfamilies, while providing an intuitive visualization of such structure.

scholarly journals Symbolic sequences and Tsallis entropy

2009 ◽  
Vol 39 (2a) ◽  
pp. 444-447 ◽  
Author(s):  
H. V. Ribeiro ◽  
E. K. Lenzi ◽  
R. S. Mendes ◽  
G. A. Mendes ◽  
L. R. da Silva
Keyword(s):  
Tsallis Entropy ◽  
Symbolic Sequences

COMPLEX DYNAMICS OF THE ELEMENTARY CELLULAR AUTOMATON RULE 54

2012 ◽  
Vol 23 (07) ◽  
pp. 1250052
Author(s):  
JUNBIAO GUAN
Keyword(s):  
Boundary Conditions ◽  
Cellular Automaton ◽  
Periodic Boundary ◽  
Complex Dynamics ◽  
Bernoulli Shift ◽  
Periodic Boundary Conditions ◽  
Self Similarity ◽  
Symbolic Sequences ◽  
Topologically Mixing ◽  
Elementary Cellular Automaton

This work deals with a discussion of complex dynamics of the elementary cellular automaton rule 54. An equation which shows some degree of self-similarity is obtained. It is shown that rule 54 exhibits Bernoulli shift and is topologically mixing on its closed invariant subsystem. Finally, many complex Bernoulli shifts are explored for the finite symbolic sequences with periodic boundary conditions.

Symbolic sequences of one-dimensional quadratic maps points

1998 ◽  
Vol 256 (3-4) ◽  
pp. 369-382 ◽  
Author(s):  
G. Pastor ◽  
M. Romera ◽  
J.C. Sanz-Martı́n ◽  
F. Montoya
Keyword(s):  
One Dimensional ◽  
Quadratic Maps ◽  
Symbolic Sequences

Delay independence of mutual-information rate of two symbolic sequences

2011 ◽  
Vol 84 (3) ◽  
Author(s):  
Jean-Luc Blanc ◽  
Laurent Pezard ◽  
Annick Lesne
Keyword(s):  
Mutual Information ◽  
Information Rate ◽  
Symbolic Sequences
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