TY - JOUR
AU - Pukenas, K.
PY - 2012/10/17
Y2 - 2021/11/27
TI - Algorithm for the Detection of Changes of the Correlation Structure in Multivariate Time Series
JF - Elektronika ir Elektrotechnika
JA - ELEKTRON ELEKTROTECH
VL - 18
IS - 8
SE -
DO - 10.5755/j01.eee.18.8.2625
UR - https://eejournal.ktu.lt/index.php/elt/article/view/2625
SP - 53-56
AB - In this research, an improved algorithm for the detection of changes of the correlation structure in multivariate time series is proposed. The starting point of the technique is a covariance matrix whose entries are the largest entries of a cross-covariance matrix which is composed of all pairs of the time series reconstructed to an <em>M</em>-dimensional phase space. Principal component analysis is performed on this maximized cross-covariance matrix, and the overall degree of synchronization among multiple-channel signals is defined, by synchronization index, as the Shannon entropy of the eigenvalue spectrum. Throughout the experiment, the effectiveness of the proposed algorithm is validated with simulated data – a network of time series generated by autoregressive models and a network of coupled chaotic Roessler oscillators.<p>DOI: <a href="http://dx.doi.org/10.5755/j01.eee.18.8.2625">http://dx.doi.org/10.5755/j01.eee.18.8.2625</a></p>
ER -