A number of different data sets are used to compare a variety of neural network training algorithms: backpropagation, quickprop, committees of backpropagation style networks and Cascade Correlation. The results are further compared with a decision tree technique, C4.5, to assess which types of problems are more suited to the different classes of inductive learning algorithms.

Abstract In this modern era, visual data transmission, processing, and analysis play a vital role in daily life. Image denoising is the process of approximately estimating original version degraded image. The presence unexpected noise (e.g., fixed, random, Gaussian) root cause degradation, which has been reduced to some extent by many linear non-linear filters based on median value. real issue ...

In this paper a topology of neural network intrusion detection system is proposed on which different backpropagation algorithms are benchmarked. The proposed methodology uses sampled data from KddCup99 data set, an intrusion detection attacks database that is a standard for the evaluation of intrusion detection systems. The performance of backpropagation algorithms implemented in batch mode, is...