A method is presented for incorporating error correction using a minimum distance measure into LR parsers. The method is suitable for use by an automatic parser-generator. State information in the LR parser stack at the point of detection of error is used to generate a set of strings which are potential repairs to the input. A string with least minimum distance from the actual input is chosen a...

Thresholding is a popular tool for segmenting grey level images. The approach is based on the assumption that object and background pixels in the image can be distinguished by their grey level values. By judiciously choosing a grey level threshold between the dominant values of object and background intensities the original grey level image can be transformed into a binary form so that the imag...

Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. In this paper, we study on the problem of clustering categorical data, where data objects are made up of non-numerical attributes. We propose MECC (Minimum Error Classification Clustering), an alternative technique for categ...

This paper describes a generalization of previous meth­ ods for constructing tree-structured belief network with hidden variables. The major new feature of the de­ scribed method is the ability to produce a tree decom­ position even when there are errors in the correlation data among the input variables. This is an important extension of existing methods since the correlational co­ efficients u...