In this paper, employing continuation theorem of the coincidence degree, and inequality technique, some sufficient conditions are derived to ensure global exponential stability and the existence of periodic solution for fuzzy cellular neural networks with time-varying delays. These results have important leading significance in the design and applications of globally stable neural networks. Mor...

By employing continuation theorem of the coincidence degree, and inequality technique, some sufficient conditions are established for the existence of periodic solution and global exponential stability of fuzzy cellular neural networks with time-varying delays. These results have important leading significance in the design and applications of globally stable neural networks. Moreover an exampl...

In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in the first and second hidden layers of El...

this paper presents a prediction model based on a new neuro-fuzzy algorithm for estimating time in construction projects. the output of the proposed prediction model, which is employed based on a locally linear neuro-fuzzy (llnf) model, is useful for assessing a project status at different time horizons. being trained by a locally linear model tree (lolimot) learning algorithm, the model is int...

In this paper we present an approach for generation and initialization of fuzzy neural networks (FNN) from data. Fuzzy neural networks are concept that integrates some features of the fuzzy logic and the artificial neural networks theory. Based on analysis of several different fuzzy neural networks models, uniform representation method is presented, and two basic types are identified: FNN based...

Over the last decade or so, significant advances have been made in two distinct technological areas: fuzzy logic and computational neutral networks. The theory of fuzzy logic provides a mathematical framework to capture the uncertainties associated with human cognitive processes, such as thinking and reasoning. Also, it provides a mathematical morphology to emulate certain perceptual and lingui...

Fuzzy neural network methods have been successfully used to diagnose many diseases. This paper uses logic-based fuzzy neural networks to diagnose breast cancer. Logic-based fuzzy neural networks can select reduced size of input subspace by selecting useful inputs. For the optimization of the input subspace and the structure of the logic-based fuzzy neural networks, genetic algorithms and gradie...