“…In [17,8], the authors report the importance of having training samples near the boundary of the acceptance region, to obtain good estimates of the parameters required for the test criterion. In order to obtain sample elements on both sides of the separating hyperplane and to retain the physically interpretability, we generate training and validation sample elements according to a normal distribution with an expected value x w , while keeping covariance matrix x .…”