ANNLYAP: MATLAB function to calculate Lyapunov exponents
AbstractThis M-file calculates Lyapunov exponents with minimum RMSE neural network. After estimation of network weights and finding network with minimum BIC, derivatives are calculated. Sum of logarithm of QR decomposition on Jacobian matrix for observations gives spectrum of Lyapunov Exponents. Using the code is very simple, it needs only an scalar time series, number of lags and number of hidden unites. Higher number of hidden units leads to more precise estimation of Lyapunov exponent, but it is time consuming for less powerful personal computers. Number of lags determines number of embedding dimensions. Therefore, please give number of lags equal to number of embedding dimension. The codes creates networks with various neurons up to user supplied value for neurons and lags up to user specified number lags. Total number of networks are equal to number of neurons times number of lags. this modeling strategy is complex but helps to user select embedding dimension based on minimum BIC.
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Bibliographic InfoSoftware component provided by Boston College Department of Economics in its series Statistical Software Components with number T7415012.
Programming language: MATLAB
Date of creation: 16 Jul 2009
Date of revision:
Contact details of provider:
Postal: Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA
Web page: http://fmwww.bc.edu/EC/
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For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F Baum).
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