Displaying similar documents to “Intelligent Nesting System”

Integrating inference and neural classification in a hybrid system for recognition tasks.

Massimo De Gregorio (1996)

Mathware and Soft Computing

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While the coupling of artificial of neural networks (ANN) and symbolic AI (SAI) is a strategy adopted in many hybrid systems, a real integration of the two methodologies has not been thoroughly investigated yet: so far, most hybrid systems have been viewed as just an engineering shortcut to solve complex problems in which one methodology alone seems too weak. In this paper, an approach to integrating ANN and SAI is presented. The basic idea explored here is that there is much more to...

Analysis of the ReSuMe learning process for spiking neural networks

Filip Ponulak (2008)

International Journal of Applied Mathematics and Computer Science

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In this paper we perform an analysis of the learning process with the ReSuMe method and spiking neural networks (Ponulak, 2005; Ponulak, 2006b). We investigate how the particular parameters of the learning algorithm affect the process of learning. We consider the issue of speeding up the adaptation process, while maintaining the stability of the optimal solution. This is an important issue in many real-life tasks where the neural networks are applied and where the fast learning convergence...

Modeling and simulation with augmented reality

Khaled Hussain, Varol Kaptan (2004)

RAIRO - Operations Research - Recherche Opérationnelle

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In applications such as airport operations, military simulations, and medical simulations, conducting simulations in accurate and realistic settings that are represented by real video imaging sequences becomes essential. This paper surveys recent work that enables visually realistic model constructions and the simulation of synthetic objects which are inserted in video sequences, and illustrates how synthetic objects can conduct intelligent behavior within a visual augmented reality. ...

Comparison of supervised learning methods for spike time coding in spiking neural networks

Andrzej Kasiński, Filip Ponulak (2006)

International Journal of Applied Mathematics and Computer Science

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In this review we focus our attention on supervised learning methods for spike time coding in Spiking Neural Networks (SNNs). This study is motivated by recent experimental results regarding information coding in biological neural systems, which suggest that precise timing of individual spikes may be essential for efficient computation in the brain. We are concerned with the fundamental question: What paradigms of neural temporal coding can be implemented with the recent learning methods?...