Amir Abolfazl Suratgar

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In this study, topographic brain mapping and wavelet transform-neural network method are used for the classification of grand mal (clonic stage) and petit mal (absence) epilepsies into healthy, ictal and interictal (EEGs). Preprocessing is included to remove artifacts occurred by blinking, wandering baseline (electrodes movement) and eyeball movement using(More)
A necessary condition for stability of a class of recurrent type-2 TSK fuzzy systems is presented. In this system, the antecedent part is indeed represented by interval Gaussian type-2 fuzzy set, and the consequent part is an ordinary nonlinear function of the system’s inputs. In the proposed method, at first a type-2 fuzzy model is established, and then an(More)
Predictive quantitative structure-activity relationship was performed on the novel4-oxo-1,4-dihydroquinoline and 4-oxo-4H-pyrido[1,2-a]pyrimidine derivatives to explore relationship between the structure of synthesized compounds and their anti-HIV-1 activities. In this way, the suitable set of the molecular descriptors was calculated and the important(More)
  • Tecnológico México Suratgar, A A Rafiei, S Taherpour, A A Babaei, A A Suratgar, S Rafiei +2 others
  • 2015
In this paper we present a new method for designing a qubit and decoder in quantum computing based on the field effect in nuclear spin. In this method, the position of hydrogen has been studied in different external fields. The more we have different external field effects and electromagnetic radiation, the more we have different distribution ratios.(More)
In this study, the problem of estimation of brain shift is addressed by which the accuracy of neuronavigation systems can be improved. To this end, the actual brain shift is considered as a Gaussian random vector with a known mean and an unknown covariance. Then, brain surface imaging is employed together with solutions of linear elastic model and the best(More)
  • Tecnológico México, Sadat Hashemipour, Samane, Abolfazl Suratgar, Amir Hoseini, Hamid +5 others
  • 2015
This paper presents a new method in order to reduce noise effect in an AC voltage reference source. The AC voltage reference source is implemented on MEMS technology. It uses capacitive MEMS technology. The reference is based on the characteristic AC current-voltage curve MEMS component. The multilayer neural network is used. The neural network (NN) uses(More)