Practical method for determining the minimum embedding dimension of a scalar time series Export

@article{citeulike:1911169, abstract = {A practical method is proposed to determine the minimum embedding dimension from a scalar time series. It has the following advantages: (1) does not contain any subjective parameters except for the time-delay for the embedding; (2) does not strongly depend on how many data points are available; (3) can clearly distinguish deterministic signals from stochastic signals; (4) works well for time series from high-dimensional attractors; (5) is computationally efficient. Several time series are tested to show the above advantages of the method.}, author = {Cao, Liangyue}, citeulike-article-id = {1911169}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/S0167-2789(97)00118-8}, citeulike-linkout-1 = {http://www.sciencedirect.com/science/article/B6TVK-3SYPTKR-4/2/504157d748a69dbb0b50e55c6670c731}, day = {1}, doi = {10.1016/S0167-2789(97)00118-8}, journal = {Physica D: Nonlinear Phenomena}, keywords = {embedded}, month = {December}, number = {1-2}, pages = {43--50}, posted-at = {2007-11-13 22:18:23}, priority = {2}, title = {Practical method for determining the minimum embedding dimension of a scalar time series}, url = {http://dx.doi.org/10.1016/S0167-2789(97)00118-8}, volume = {110}, year = {1997} }

TY - JOUR ID - citeulike:1911169 L3 - citeulike-article-id:1911169 N2 - A practical method is proposed to determine the minimum embedding dimension from a scalar time series. It has the following advantages: (1) does not contain any subjective parameters except for the time-delay for the embedding; (2) does not strongly depend on how many data points are available; (3) can clearly distinguish deterministic signals from stochastic signals; (4) works well for time series from high-dimensional attractors; (5) is computationally efficient. Several time series are tested to show the above advantages of the method. IS - 1-2 JF - Physica D: Nonlinear Phenomena EP - 50 TI - Practical method for determining the minimum embedding dimension of a scalar time series VL - 110 SP - 43 KW - embedded AU - Cao, Liangyue PY - 1997/12/01/ UR - http://dx.doi.org/10.1016/S0167-2789(97)00118-8 ER -