In this paper, we consider each neural network as a point in a multi-dimensional problem space and suggest a crossover that locates the central point of a number of neural networks...
Advances in data collection technologies allow accumulation of large and high dimensional datasets and provide opportunities for learning high quality classification and regression...
This paper considers the robust stability of neural networks with multiple delays. Based on Lyapunov stability theory and linear matrix inequality technique, some new delay indepe...
The research of impacts between the Internet stock news (ISN) and the stock price movements emerges with the era of the popular usage of the Internet. In this paper, first, the ISN...
Abstract. The performance of financial forecasting with neural networks dependents on the particular training set. We design mean-change-point test to divide the original dataset i...
Contextual information and a priori knowledge play important roles in image segmentation based on neural networks. This paper proposed a method for including contextual information...
A system that segments and labels tabla strokes from real performances is described. Performance is evaluated on a large database taken from three performers under different recor...
We introduce a novel method for relational learning with neural networks. The contributions of this paper are threefold. First, we introduce the concept of relational neural networ...
In this paper, a neural network based approach to visualize performance data of a GSM network is presented. The proposed approach consists of several steps. First, a suitable propo...
This paper presents a novel texture segmentation method using Bayesian estimation and neural networks. Multi-scale wavelet coefficients and the context information extracted from n...