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We propose a built-in scheme for generating all patterns of a given deterministic test set T. The scheme is based on grouping the columns of T, so that in each group of columns the number ri of unique representatives (row subvectors) as well as their product R over all such groups is kept at a minimum. The representatives of each group (segment) are then generated by a small finite state machine (FSM)...
Error correction is an effective way to mitigate fault attacks in cryptographic hardware. It is also an effective solution to soft errors in deep sub-micron technologies. To this end, we present a systematic method for designing single error correcting (SEC) and double error detecting (DED) finite field (Galoisfield) multipliers over GF(2m). The detection and correction are done on-line. We use multiple...
Categorization of scenes is a fundamental process of human vision that allows us to efficiently and rapidly analyze our surroundings. Scene classification, the classification of images into semantic categories (e.g., coast, mountains, highways and streets) is a challenging and important problem nowadays. This paper is classifying the scenes using support vector machine with radial basis kernel with...
We present a preprocessing algorithm to make certain polynomial algorithms strongly polynomial. The running time of some of the known combinatorial optimization algorithms depends on the size of the objective function w. Our preprocessing algorithm replaces w by an integral valued w whose size is polynomially bounded in the size of the combinatorial structure and which yields the same set of optimal...
We show that there can be no computationally tractable description by linear inequalities of the polyhedron associated with any NP-complete combinatorial optimization problem unless NP = co-NP -- a very unlikely event. We also apply the ellipsoid method for linear programming to show that a combinatorial optimization problem is solvable in polynomial time if and only if it admits a small generator...
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