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Although a number of normalized edit distances presented so far may offer good performance in some applications, none of them can be regarded as a genuine metric between strings because they do not satisfy the triangle inequality. Given two strings X and Y over a finite alphabet, this paper defines a new normalized edit distance between X and Y as a simple(More)
Based on the “convexly separable” concept, we present a solid geometric theory and a new general framework to design piecewise linear classifiers for two arbitrarily complicated nonintersecting classes by using a “multiconlitron,” which is a union of multiple conlitrons that comprise a set of hyperplanes or linear functions(More)
We study the problem of how to recognize a person only by his eyebrow based on hidden Markov models (HMM). By experiments on a small-scale eyebrow image database taken from 27 subjects, we show that our HMM-based eyebrow recognition method can achieve the highest accuracy of 92.6%, based on the relation of its accuracy to the number of observation symbols(More)
The traditional UPGMA (Unweighted Pair Group Method with Arithmetic Mean) sometimes derives two or more topologies of “tie trees” from a single data set, depending on the order of data entry. This paper presents an improved algorithm for UPGMA, namely, UMGMA (Unweighted Multiple Group Method with Arithmetic Mean), which can produce a unique(More)
The paper presents an accurate stochastic model for transfer latency of short-lived Web-like TCP flows with random packet losses. Our model characterizes a data transfer in alternating cycles, with TCP state information carried over from one cycle to the next. Simulation experiments show that our model matches simulation results for short-lived flows better(More)