9 Result(s)
within
Conference Paper
José Alí Moreno
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Chapter and Conference Paper
Robot Path Planning in Kernel Space
We present a new approach to path planning based on the properties of the minimum enclosing ball (MEB) in a reproducing kernel space. The algorithm is designed to find paths in high-dimensional continuous spac...
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Chapter and Conference Paper
Cellular Automata and Its Application to the Modeling of Vehicular Traffic in the City of Caracas
In this paper an emergent microscopic traffic model based on a cellular automaton is presented. The model is part of a vehicular traffic study recently initiated in the city of Caracas in Venezuela. The propos...
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Chapter and Conference Paper
Heuristic Algorithm for Robot Path Planning Based on a Growing Elastic Net
A simple effective method for path planning based on a growing self-organizing elastic neural network, enhanced with a heuristic for the exploration of local directions is presented. The general problem is to ...
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Chapter and Conference Paper
An Efficient Heuristic for the Traveling Salesman Problem Based on a Growing SOM-like Algorithm
A growing self-organizing (SOM) neural network, enhanced with a local search heuristic is proposed as an efficient traveling salesman problem solver. A ring structure of processing units is evolved in time wit...
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Chapter and Conference Paper
The Hopfield Associative Memory Network: Improving Performance with the Kernel “Trick”
This paper provides a new insight into the training of the Hopfield associative memory neural network by using the kernel theory drawn from the work on kernel learning machines and related algorithms. The kern...
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Chapter and Conference Paper
Kernel Based Method for Segmentation and Modeling of Magnetic Resonance Images
In this paper we propose a method for segmenting structures in Magnetic Resonance Images (MRI) using the well known kernel Adatron algorithm. The method allows the segmentation in feature space of 2D structure...
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Chapter and Conference Paper
The Kernel Hopfield Memory Network
The kernel theory drawn from the work on learning machines is applied to the Hopfield neural network. This provides a new insight into the workings of the neural network as associative memory. The kernel “tric...
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Chapter and Conference Paper
Application of Learning Machine Methods to 3D Object Modeling
Three different machine learning algorithms applied to 3D object modeling are compared.The methods considered, (Support Vector Machine, Growing Grid and Kohonen Feature Map) were compared in their capacity to ...
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Chapter and Conference Paper
Border Detection in Digital Images With a Simple Cellular Automata Rule
This paper presents the application of two-dimensional cellular automata to the problem of border detection in digital images. A simple dynamical rule for the cellular automata is proposed that maps an initial...
