972 resultados para Telescope space debris satellite spectroscopy tracking photometry NASA ASI


Relevância:

40.00% 40.00%

Publicador:

Resumo:

Mode of access: Internet.

Relevância:

40.00% 40.00%

Publicador:

Resumo:

Mode of access: Internet.

Relevância:

40.00% 40.00%

Publicador:

Resumo:

Cover title.

Relevância:

40.00% 40.00%

Publicador:

Resumo:

Mode of access: Internet.

Relevância:

40.00% 40.00%

Publicador:

Resumo:

"The material in this booklet is a reprint of a portion of that which was prepared by NASA's Office of Space Science and Applications for presentation to the Congress."

Relevância:

40.00% 40.00%

Publicador:

Resumo:

We propose a novel interpretation and usage of Neural Network (NN) in modeling physiological signals, which are allowed to be nonlinear and/or nonstationary. The method consists of training a NN for the k-step prediction of a physiological signal, and then examining the connection-weight-space (CWS) of the NN to extract information about the signal generator mechanism. We de. ne a novel feature, Normalized Vector Separation (gamma(ij)), to measure the separation of two arbitrary states i and j in the CWS and use it to track the state changes of the generating system. The performance of the method is examined via synthetic signals and clinical EEG. Synthetic data indicates that gamma(ij) can track the system down to a SNR of 3.5 dB. Clinical data obtained from three patients undergoing carotid endarterectomy of the brain showed that EEG could be modeled (within a root-means-squared-error of 0.01) by the proposed method, and the blood perfusion state of the brain could be monitored via gamma(ij), with small NNs having no more than 21 connection weight altogether.