Zobrazeno 1 - 10
of 62
pro vyhledávání: '"Passamante, A."'
Publikováno v:
Physica D: Nonlinear Phenomena. 96:100-109
In this work we characterize data using the repeatability of similar data sequences (of length of the order of 5–100 times the embedding dimension) which are found in the data itself. A system which is constrained to move on a compact region of pha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a22a697eefd46fd1fda2ceef37d6b140
https://doi.org/10.1016/0167-2789(96)00015-2
https://doi.org/10.1016/0167-2789(96)00015-2
Publikováno v:
Physica D: Nonlinear Phenomena. 79:320-334
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4b74e4aaf8b09465eff831969a9876d9
https://doi.org/10.1016/s0167-2789(05)80012-0
https://doi.org/10.1016/s0167-2789(05)80012-0
Publikováno v:
International Journal of Bifurcation and Chaos. :485-490
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::93121a284620a479b903f68ba05b02df
https://doi.org/10.1142/s0218127493000398
https://doi.org/10.1142/s0218127493000398
Publikováno v:
International Journal of Bifurcation and Chaos. :797-802
The effect of the chosen forecasting method on the measured predictability of a noisy recurrent time series is investigated. Situations where the length of the time series is limited, and where the level of corrupting noise is significant are emphasi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d029cdb4e7cbdc0f86e0ba1de4f82665
https://doi.org/10.1142/s0218127493000738
https://doi.org/10.1142/s0218127493000738
Publikováno v:
Physica D: Nonlinear Phenomena. 58:1-9
Backpropagating neural networks are used to reconstruct the attractors of two low-dimensional chaotic systems using small input sets of noise-corrupted data. The nets are able to reconstruct attractors that are visually similar to, and have the same
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5c2cd2b022da030a74b7a23a5b7c196d
https://doi.org/10.1016/0167-2789(92)90098-8
https://doi.org/10.1016/0167-2789(92)90098-8
Publikováno v:
Physica D: Nonlinear Phenomena. 54:85-97
Correlation functions of up to fourth order are investigated numerically in search of a reliable window for embedding or reconstructing chaotic flows by the method of time delays. A number of these higher-order correlations display coincident extrema
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bd60713f1cd679606b69e7220b9d7289
https://doi.org/10.1016/0167-2789(91)90110-u
https://doi.org/10.1016/0167-2789(91)90110-u
Autor:
A. Passamante, Mary Eileen Farrell
Publikováno v:
Physical Review A. 43:5268-5274
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d41bd4f3034e8dde7439432d28d4267c
https://doi.org/10.1103/physreva.43.5268
https://doi.org/10.1103/physreva.43.5268
Publikováno v:
Physical Review A. 41:5325-5332
An algorithm to estimate the average local intrinsic dimension (〈${\mathit{d}}_{\mathrm{LID}}$〉) of an attractor using signal versus noise separation methods based on information-theoretic criteria is explored in this work. Using noisy sample dat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d117e9b8efe468b130b65e7b1aa31d6
https://doi.org/10.1103/physreva.41.5325
https://doi.org/10.1103/physreva.41.5325
Autor:
T. Hediger, A. Passamante
Publikováno v:
ICASSP
The use of spectrum estimators as preprocessors to classification decisions is discussed in this paper. The classification performance using features chosen after spectrum estimation is measured by estimating the Bayes error, obtained by using the kt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::456cd8e7395f816d2cf80eeaefdd7715
https://doi.org/10.1109/icassp.1985.1168336
https://doi.org/10.1109/icassp.1985.1168336
Publikováno v:
Proceedings of the 32nd Midwest Symposium on Circuits and Systems.
The problem of identifying chaotic systems is considered. Dimensions of chaotic attractors are briefly discussed. An algorithm based on the attractor's local intrinsic dimensionality (LID) is discussed and implemented using singular value decompositi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b27d4eb71927b2ce25957519330d64a1
https://doi.org/10.1109/mwscas.1989.101871
https://doi.org/10.1109/mwscas.1989.101871