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» An NP-Hardness Result for Nonlinear Systems
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APPINF
2003
13 years 9 months ago
Preventing Computational Chaos in Asynchronous Neural Networks
One of the primary advantages of artificial neural networks is their inherent ability to perform massively parallel, nonlinear signal processing. However, the asynchronous dynamics...
Jacob Barhen, Vladimir Protopopescu
CORR
2006
Springer
101views Education» more  CORR 2006»
13 years 7 months ago
Fast computation of power series solutions of systems of differential equations
We propose algorithms for the computation of the first N terms of a vector (or a full basis) of power series solutions of a linear system of differential equations at an ordinary ...
Alin Bostan, Frédéric Chyzak, Fran&c...
CDC
2008
IEEE
122views Control Systems» more  CDC 2008»
14 years 2 months ago
Geometrical conditions for output depending observability normal form
— We give geometrical conditions, which guarantee the existence of a diffeomorphism in order to transform a nonlinear system without inputs into a canonical normal form depending...
Gang Zheng, Driss Boutat, Jean-Pierre Barbot
CDC
2010
IEEE
100views Control Systems» more  CDC 2010»
13 years 2 months ago
Impulsive systems triggered by superposed renewal processes
We consider impulsive systems with several reset maps triggered by independent renewal processes, i.e., the intervals between jumps associated with a given reset map are identicall...
Duarte Antunes, João Pedro Hespanha, Carlos...
ICTAI
2005
IEEE
14 years 1 months ago
Hybrid Learning Neuro-Fuzzy Approach for Complex Modeling Using Asymmetric Fuzzy Sets
A hybrid learning neuro-fuzzy system with asymmetric fuzzy sets (HLNFS-A) is proposed in this paper. The learning methods of random optimization (RO) and least square estimation (...
Chunshien Li, Kuo-Hsiang Cheng, Jiann-Der Lee