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Is there any geometrical information in the nervous system?

Jafari S, Hashemi Golpayegani SM, Gharibzadeh S - Front Comput Neurosci (2013)

View Article: PubMed Central - PubMed

Affiliation: Biomedical Engineering Faculty, Amirkabir University of Technology Tehran, Iran.

No MeSH data available.


Related in: MedlinePlus

(A) Two time series obtained from two different Logistic maps. (B) Those two time series embedded in the state space. As can be seen while recognizing the difference between them is not such easy in the time domain (both are random-like), they have two ordered and easily distinguishable pattern in the state space.
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Figure 1: (A) Two time series obtained from two different Logistic maps. (B) Those two time series embedded in the state space. As can be seen while recognizing the difference between them is not such easy in the time domain (both are random-like), they have two ordered and easily distinguishable pattern in the state space.

Mentions: If we obtain one time series from each of them, as can be seen in Figure 1A, they are both random-like and recognizing the difference between them seems difficult in the time domain. However, they have two ordered and easily distinguishable patterns in the state space (Figure 1B).


Is there any geometrical information in the nervous system?

Jafari S, Hashemi Golpayegani SM, Gharibzadeh S - Front Comput Neurosci (2013)

(A) Two time series obtained from two different Logistic maps. (B) Those two time series embedded in the state space. As can be seen while recognizing the difference between them is not such easy in the time domain (both are random-like), they have two ordered and easily distinguishable pattern in the state space.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3757320&req=5

Figure 1: (A) Two time series obtained from two different Logistic maps. (B) Those two time series embedded in the state space. As can be seen while recognizing the difference between them is not such easy in the time domain (both are random-like), they have two ordered and easily distinguishable pattern in the state space.
Mentions: If we obtain one time series from each of them, as can be seen in Figure 1A, they are both random-like and recognizing the difference between them seems difficult in the time domain. However, they have two ordered and easily distinguishable patterns in the state space (Figure 1B).

View Article: PubMed Central - PubMed

Affiliation: Biomedical Engineering Faculty, Amirkabir University of Technology Tehran, Iran.

No MeSH data available.


Related in: MedlinePlus