The nondispersive per-sample channel model for the optical fiber is considered. Under certain smoothness assumptions, problem of finding minimum amount noise energy that can render two different input points indistinguishable formulated. This then taken as a measure distance between in alphabet. Using machinery optimal control theory, necessary conditions describe minimum-energy trajectories ar...

Face recognition provides broad access to several public devices, so it is essential in the midst of today's technology boom. Human face recognizing has challenge using uncomplicated and straightforward algorithms quickly, memory specifications are not too high, otherwise results quality accurate. combination edge detection Canberra distance can be recommended for applications that require fast...

The attack price of higher order side channel attacks (HOSCA) grows exponentially with the mask order. When is larger than 3, HOSCA can be inapplicable. In light this, distance similarity measure based profiling (DSMPA) proposed. DSMPA, leakage property masks characterised in a scenario and so called templates obtained. Then, DSM used to recover values templates. With recovered, effect masking ...

To evaluate clustering results is a significant part of cluster analysis. Since there are no true class labels for in typical unsupervised learning, many internal validity indices (CVIs), which use predicted and data, have been created. Without labels, to design an effective CVI as difficult create method. And it crucial more CVIs because universal that can be used measure all datasets specific...

A bstract We introduce a new unbinned two sample test statistic sensitive to CP violation utilizing the optimal transport plan associated with Wasserstein (earth mover’s) distance. The efficacy of is shown via examples asymmetric distributions varying sizes: Dalitz B 0 → K + π − and D decays. windowed version distance have comparable sensitivity as commonly used energy statistic, but also retai...

Applications in data science, shape analysis, and object classification frequently require comparison of probability distributions defined on different ambient spaces. To accomplish this, one requires a notion distance given class metric measure spaces—that is, compact spaces endowed with measures. Such distances are typically as comparisons between space invariants, such (also referred to dist...