When training classifiers, presence of noise can severely harm their performance. In this paper, we focus on “non-class” attribute noise and we consider how a frequent fault-t...
We propose a simple pulse-amplitude modulation (PAM)-based coded modulation scheme that overcomes two major constraints of power line channels, viz., severe insertion-loss and impu...
This paper describes a model and a setup for emulating fractal and multifractal noise for the measurement and evaluation of performance of ZigBee mesh networks intended for harsh ...
Several published reports show that instancebased learning algorithms yield high classification accuracies and have low storage requirements during supervised learning application...
Learning an unknown halfspace (also called a perceptron) from labeled examples is one of the classic problems in machine learning. In the noise-free case, when a halfspace consist...