Abstract. Probabilistic Neural Networks (PNNs) constitute a promising methodology for classification and prediction tasks. Their performance depends heavily on several factors, su...
Vasileios L. Georgiou, Sonia Malefaki, Konstantino...
This paper presents a novel approach to financial time series analysis and prediction. It is mainly devoted to the problem of forecasting university facility and administrative co...
Tomasz G. Smolinski, Darrel L. Chenoweth, Jacek M....
In this paper, a neural network scheme is presented for modeling VBR MPEG-2 video sources. In particular, three non linear autoregressive models (NAR) are proposed to model the ag...
Anastasios D. Doulamis, Nikolaos D. Doulamis, Stef...
We propose a new approach to fault detection and diagnosis in third-generation (3G) cellular networks using competitive neural algorithms. For density estimation purposes, a given ...
This paper proposes a simple methodology to construct an iterative neural network which mimics a given chaotic time series. The methodology uses the Gamma test to identify a suita...
Antonia J. Jones, Steve Margetts, Peter Durrant, A...