Search results for "Cellular neural network"
showing 6 items of 6 documents
Global exponential stability of delayed Markovian jump fuzzy cellular neural networks with generally incomplete transition probability
2014
The problem of global exponential stability in mean square of delayed Markovian jump fuzzy cellular neural networks (DMJFCNNs) with generally uncertain transition rates (GUTRs) is investigated in this paper. In this GUTR neural network model, each transition rate can be completely unknown or only its estimate value is known. This new uncertain model is more general than the existing ones. By constructing suitable Lyapunov functionals, several sufficient conditions on the exponential stability in mean square of its equilibrium solution are derived in terms of linear matrix inequalities (LMIs). Finally, a numerical example is presented to illustrate the effectiveness and efficiency of our res…
Dynamic Pattern Recognition in Sport by Means of Artificial Neural Networks
2008
Behavioural processes like those in sports, motor activities or rehabilitation are often the object of optimization methods. Such processes are often characterized by a complex structure. Measurements considering them may produce a huge amount of data. It is an interesting challenge not only to store these data, but also to transform them into useful information. Artificial Neural Networks turn out to be an appropriate tool to transform abstract numbers into informative patterns that help to understand complex behavioural phenomena. The contribution presents some basic ideas of neural network approaches and several examples of application. The aim is to give an impression of how neural meth…
Neural networks for animal science applications: Two case studies
2006
Abstract Artificial neural networks have shown to be a powerful tool for system modelling in a wide range of applications. In this paper, we focus on neural network applications to intelligent data analysis in the field of animal science. Two classical applications of neural networks are proposed: time series prediction and clustering. The first task is related to the prediction of weekly milk production in goat flocks, which includes a knowledge discovery stage in order to analyse the relative relevance of the different variables. The second task is the clustering of goat flocks; it is used to analyse different livestock surveys by using self-organizing maps and the adaptive resonance theo…
A Reconfigurable Neural Environment on Active Networks
2000
This paper proposes the deployment of a neural network computing environment on Active Networks. Active Networks are packet-switched computer networks in which packets can contain code fragments that are executed on the intermediate nodes. This feature allows the injection of small pieces of codes to deal with computer network problems directly into the network core, and the adoption of new computing techniques to solve networking problems. The goal of our project is the adoption of a distributed neural network for approaching tasks which are specific of the computer network environment. Dynamically reconfigurable neural networks are spread on an experimental wide area backbone of active no…
The computational power of continuous time neural networks
1997
We investigate the computational power of continuous-time neural networks with Hopfield-type units. We prove that polynomial-size networks with saturated-linear response functions are at least as powerful as polynomially space-bounded Turing machines.
A CNN Adaptive Model to Estimate PM10 Monitoring
2006
In this work we introduce a model for studying the distribution and control of atmospheric pollution from PM10. The model is based on the use of a cellular neural network (CNN) and more precisely on the integration of the mass-balance equation; at the same time it simulates the scenario regarding a planar grid describing the whole studied area (the city of Palermo) by means of a CNN and a set of Bayesian networks. The CNN allows us to define a grid system whose dynamic evolution is a redefinition of the diffusion equation that considers contributions coming from near cells for each element of the grid. Dynamics of each cell is influenced by meteorological effects and by parameters related t…