This paper considers the robust D-stability margin problem under polynomic structured real parametric uncertainty. Based on the work of De Gaston and Safonov (1988), we have developed techniques such as, a parallel frequency sweeping strategy, different domain splitting schemes, which significantly reduce the computational complexity and guarantee the convergence.

In our work we address limitations in the state-of-the-art in idiom type identification. We investigate different approaches for a lexical fixedness metric, a component of the state-of-the-art model. We also show that our Machine Learning based approach to the idiom type identification task achieves an F1-score of 0.85, an improvement of 11 points over the state-of-the-art.

Various problems in nonnegative quadratic programming arise in the training of large margin classifiers. We derive multiplicative updates for these problems that converge monotonically to the desired solutions for hard and soft margin classifiers. The updates differ strikingly in form from other multiplicative updates used in machine learning. In this paper, we provide complete proofs of conver...

Simultaneous risk-limiting audits of a collection of contests have a known minimum chance of leading to a full hand count if any outcomes are wrong. They are generally performed in stages. Each stage involves drawing a sample of ballots, comparing a hand count of the votes on those ballots with the original count, and assessing the evidence that the original outcomes agree with the outcomes tha...

In this paper, we evaluate the stability margin of a Fiat Dedra engine model to explore possible applications of theoretical achievements in the parametric approach to robust control problems. The study is based on two versions of the model with uncertainties. One is the original model, which has a multilinear characteristic polynomial, while the other is an affine-linearized model which is obt...

In this paper, we investigate the read operation of memristor-based memories. We analyze the sneak paths problem and provide a noise margin metric to compare the various solutions proposed in the literature. We also analyze the power consumption associated with these solutions. Moreover, we study the effect of the aspect ratio of the memory array on the sneak paths. Finally, we introduce a new ...

Sauer’s Lemma is extended to classes H of binary-valued functions on [n] = {1, . . . , n} which have a margin less than or equal to N on x ∈ [n], where the margin μh(x) of a binary valued function h at a point x ∈ [n] is defined as the largest nonnegative integer a such that h is constant on the interval Ia(x) = [x−a, x+a] ⊆ [n]. Estimates are obtained for the cardinality of classes of binary v...

Previous results have shown disappointing performance when porting a parser trained on one domain to another domain where only a small amount of data is available. We propose the use of data-defined kernels as a way to exploit statistics from a source domain while still specializing a parser to a target domain. A probabilistic model trained on the source domain (and possibly also the target dom...

This paper details a systematic method for significantly improving the noise margins of very fast threshold gates. The method is based on adding nonlinear terms determined from the Boolean form of the threshold function to be implemented. Simulation results support our theoretical claims. Finally, two methods for drastically reducing the dissipated power of such threshold gates down to <50%, an...

Mobile manipulators operating in field environments will be required to apply large forces, or manipulate large loads, and to perform such tasks on uneven terrain which may cause the system to approach, or reach, a dangerous tipover instability. To avoid tipover in an automatic system, or to provide a human operator with an indication of proximity to tipover, it is necessary to define a measure...