We introduce a nonlinear refinement subdivision scheme based on median-interpolation. The scheme constructs a polynomial interpolating adjacent block medians of an underlying object. The interpolating polynomial is then used to impute block medians at the next finer triadic scale. Perhaps surprisingly, expressions for the refinement operator can be obtained in closed-form for the scheme interpo...

Contingency tables often arise from collecting patient data and from lab experiments. A typical question to be answered based on a contingency table is whether the rows or the columns show a significant difference. Median Polish (MP) is fast becoming a prefered way to analyse contingency tables based on a simple additive model. Often, the data need to be transformed before applying the MP algor...

In this paper, a new nonlinear median based filtering technique is introduced for the enhancement of medical images that are highly contaminated by impulse noise. The proposed Detail Preserving Fast Median Filtering (DPFMF) technique is more effective in eliminating fixed value impulse noise and preserving the image details. The filter replaces a corrupted pixel by the median value of the fast ...

Feature subset selection is an essential preprocessing task in data mining. This paper presents a new method called Extended Fuzzy Relative Information Measure for Boundary Samples (EFRIMBS) for dealing with supervised feature subset selection. The proposed algorithm uses boundary samples instead of full set of samples. First, Discretization algorithms such as K-Means, Fuzzy C Means and Median ...

In this contribution, we present a constructive method to derive flat sampled-data models for continuous-time systems through an implicit Euler-discretization. We show how the model can be used subsequently flatness-based controller design, and illustrate our results with well-known planar VTOL aircraft example.

classical explicit finite difference schemes are unsuitable for the solution of the famous black-scholes partial differential equation, since they impose severe restrictions on the time step. furthermore, they may produce spurious oscillations in the solution. we propose a new scheme that is free of spurious oscillations and guarantees the positivity of the solution for arbitrary stepsizes. the...

Discretization algorithms have played an important role in data mining and knowledge discovery. They not only produce a concise summarization of continuous attributes to help the experts understand the data more easily, but also make learning more accurate and faster. In this paper, we propose a static, global, incremental, supervised and top-down discretization algorithm based on Class-Attribu...