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Mostrando ítems 21-27 de 27
Artículo
Using membrane computing for effective homology
(2012)
Effective Homology is an algebraic-topological method based on the computational concept of chain homotopy equivalence on a cell complex. Using this algebraic data structure, Effective Homology gives answers to some important ...
Ponencia
Tissue-like P Systems Without Environment
(Fénix Editora, 2010)
In this paper we present a tissue-like P systems model with cell division the environment has been replaced by an extra cell. In such model, we present a uniform family of recognizer P systems which solves the Subset Sum ...
Artículo
Semantics of deductive databases with spiking neural P systems
(Elsevier, 2018)
The integration of symbolic reasoning systems based on logic and connectionist systems based on thefunctioning of living neurons is a vivid research area in computer science. In the literature, one can findmany efforts ...
Artículo
A parallel algorithm for skeletonizing images by using spiking neural P systems
(Elsevier, 2013-09)
Skeletonization is a common type of transformation within image analysis. In general, the image B is a skeleton of the black and white image A, if the image B is made of fewer black pixels than the image A, it does preserve ...
Ponencia
Cell Complexes and Membrane Computing for Thinning 2D and 3D Images
(Fénix Editora, 2012)
In this paper, we show a new example of bridging Algebraic Topology, Membrane Computing and Digital Images. In [24], a new algorithm for thinning multidimensional black and white digital images by using cell complexes ...
Artículo
Two-hidden-layer Feedforward Neural Networks are Universal Approximators: A Constructive Approach
(Cornell University, 2019)
It is well known that Artificial Neural Networks are universal approximators. The classical result proves that, given a continuous function on a compact set on an n-dimensional space, then there exists a one-hidden-layer ...
Artículo
Representative datasets for neural networks
(Elsevier, 2018)
Neural networks present big popularity and success in many fields. The large training time process problem is a very important task nowadays. In this paper, a new approach to get over this issue based on reducing dataset ...