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NC
2010
146views Neural Networks» more  NC 2010»
13 years 2 months ago
Petri nets for modelling metabolic pathways: a survey
Abstract. In the last fifteen years, several research efforts have been directed towards the representation and the analysis of metabolic pathways by using Petri nets. The goal o...
Paolo Baldan, Nicoletta Cocco, Andrea Marin, Marta...
NC
2010
150views Neural Networks» more  NC 2010»
13 years 2 months ago
Deterministic and stochastic P systems for modelling cellular processes
This paper presents two approaches based on metabolic and stochastic P systems, together with their associated analysis methods, for modelling biological systems and illustrates th...
Marian Gheorghe, Vincenzo Manca, Francisco Jos&eac...
NC
2010
179views Neural Networks» more  NC 2010»
13 years 2 months ago
Representation before computation
My main objective is to point out a fundamental weakness in the conventional conception of computation and suggest a promising way out. This weakness is directly related to a gross...
Lev Goldfarb
NC
2010
141views Neural Networks» more  NC 2010»
13 years 2 months ago
On spiking neural P systems
Oscar H. Ibarra, Mario J. Pérez-Jimé...
ISNN
2010
Springer
13 years 2 months ago
Pruning Training Samples Using a Supervised Clustering Algorithm
As practical pattern classification tasks are often very-large scale and serious imbalance such as patent classification, using traditional pattern classification techniques in ...
Minzhang Huang, Hai Zhao, Bao-Liang Lu
ISNN
2010
Springer
13 years 2 months ago
MULP: A Multi-Layer Perceptron Application to Long-Term, Out-of-Sample Time Series Prediction
Abstract. A forecasting approach based on Multi-Layer Perceptron (MLP) Artificial Neural Networks (named by the authors MULP) is proposed for the NN5 111 time series long-term, out...
Eros Pasero, Giovanni Raimondo, Suela Ruffa
ISNN
2010
Springer
13 years 2 months ago
Extension of the Generalization Complexity Measure to Real Valued Input Data Sets
Abstract. This paper studies the extension of the Generalization Complexity (GC) measure to real valued input problems. The GC measure, defined in Boolean space, was proposed as a...
Iván Gómez, Leonardo Franco, Jos&eac...
ISNN
2010
Springer
13 years 2 months ago
Particle Swarm Optimization Based Learning Method for Process Neural Networks
Abstract. This paper proposes a new learning method for process neural networks (PNNs) based on the Gaussian mixture functions and particle swarm optimization (PSO), called PSO-LM....
Kun Liu, Ying Tan, Xingui He
INFORMATICALT
2010
91views more  INFORMATICALT 2010»
13 years 2 months ago
An Expansion of the Neural Network Theory by Introducing Hebb Postulate
In the presented paper, some issues of the fundamental classical mechanics theory in the sense of Ising physics are introduced into the applied neural network area. The expansion o...
Algis Garliauskas