In this paper, a novel scheme is proposed to adapt the gains of a sliding mode controller (SMC) so that the problems faced in its practical implementations as a motion controller are overcome. A L yapunov function is selected for the design of the SMC and an MIT rule is used for gain adaptation. The criterion that is minimized for gain adaptation is selected as the sum of the squares of the con...

The Conventional control approach may not be suitable for non-linear systems and for the systems with considerable parameter variations over a period of time. On the other hand adaptive control techniques proved to be a convenient tool in dealing with the above said systems. The Model Reference Adaptive Systems (MRAS) with performance specifications given in terms of reference model is tried fo...

Abstract: New datamining techniques are developed for generating frequent episode rules of traffic events. These episode rules are used to distinguish anomalous sequences of TCP, UDP, or ICMP connections from normal traffic episodes. Fundamental rule pruning techniques are introduced to reduce the search space by 40-70%. Our approach accelerates the entire process of machine learning and profil...

Adaptive control is a very appealing technology, at least in principle. Yet its use has been conditioned by an attitude of distrustfulness on the part of some practitioners. In this paper, we review some concepts, the isolation of which was necessary to engender confidence in the technology. These include the unpredictable failure of the MIT rule; the bursting phenomenon, and how to prevent it;...

The Conventional control approach may not be suitable for non-linear systems and for the systems with considerable parameter variations over a period of time. On the other hand adaptive control techniques proved to be a convenient tool in dealing with the above said systems. The Model Reference Adaptive Systems (MRAS) with performance specifications given in terms of reference model is tried fo...

MOTIVATION Changes in the normal rhythm of a human heart may result in different cardiac arrhythmias, which may be immediately fatal or cause irreparable damage to the heart sustained over long periods of time. Therefore, the ability to automatically identify arrhythmias from ECG recordings is important for clinical diagnosis and treatment. In this article, classification by using associative P...

Presented is a paradigm of how a design concept can be converted into a system of production rules to generate designs. The rules are expressed by the means of shape grammar formalism. The paradigm demonstrates how porosity a concept transferred from biology, medicine and organic chemistry was implemented by architect Steven Holl and his team in designing the 350-unit student residence Simmons ...

We study the quark angular momentum distribution in the nucleon within a light-front covariant quark model. Special emphasis is put into the orbital angular momentum: a quantity which is very sensitive to the relativistic treatment of the spin in a light-front dynamical approach. Discrepancies with the predictions of the low-energy traditional quark models where relativistic spin effects are ne...

This paper addresses the problem of language distribution estimation from unlabeled data. We present a new algorithm that treats automated classifier identification outputs as likelihoods and iteratively applies Bayes’ rule to reclassify the data using successively improving distribution estimates as “priors”. Experimental results using the MIT LL submission to the NIST LRE07 evaluation show si...

One of the most promising ways of improving the performance of deep convolutional neural networks is by increasing the number of convolutional layers. However, adding layers makes training more difficult and computationally expensive. In order to train deeper networks, we propose to add auxiliary supervision branches after certain intermediate layers during training. We formulate a simple rule ...