Zobrazeno 1 - 10
of 176
pro vyhledávání: '"Narasimhan, Sundararajan"'
Publikováno v:
Cognitive Computation. 15:751-764
Autor:
Subbaraju, Vigneshwaran, Suresh, Mahanand Belathur, Sundaram, Suresh, Narasimhan, Sundararajan
Publikováno v:
In Medical Image Analysis January 2017 35:375-389
Publikováno v:
Unmanned Systems.
Autor:
Subbaraju, Vigneshwaran, Sundaram, Suresh, Narasimhan, Sundararajan, Suresh, Mahanand Belathur
Publikováno v:
In Expert Systems With Applications 1 December 2015 42(22):8775-8790
Publikováno v:
IEEE Transactions on Systems, Man, and Cybernetics: Systems. 52:1003-1013
The plants of nano air vehicles (NAVs) are generally unstable, adversely coupled, and uncertain. Besides, the autopilot hardware of a NAV has limited sensing and computational capabilities. Hence, these vehicles need a single controller referred to a
Publikováno v:
2022 IEEE Symposium Series on Computational Intelligence (SSCI).
Publikováno v:
IEEE transactions on cybernetics.
This article presents a new approach for providing an interpretation for a spiking neural network classifier by transforming it to a multiclass additive model. The spiking classifier is a multiclass synaptic efficacy function-based leaky-integrate-fi
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 20:1659-1668
In this paper, a cognitive decision-making architecture for dynamic airspace sectorization (CDAS) to handle increasing traffic flow and provide an efficient decision making process for operations is presented. The main objective of CDAS is to determi
Publikováno v:
Engineering Applications of Artificial Intelligence. 110:104717
This paper presents a coupled, neural network-aided longitudinal cruise and lateral path-tracking controller for an autonomous vehicle with model uncertainties and experiencing unknown external disturbances. Using a feedback error learning mechanism,
Publikováno v:
Information Sciences. :1-15
In this paper, a new multi-objective optimization algorithm in a multi-scale framework with faster convergence characteristics is presented, referred to as the Pareto-Aware DIviding RECTangles ( PA-DIRECT ) method. PA-DIRECT follows the Multi-scale S