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- W2034302609 abstract "This paper describes a technique designed to examine a set of patterns (biologic waveforms) and decide if there are groups of patterns satisfying a given criterion of similarity. If such groups are found, patterns representative of identified groups are calculated and returned as patterns typical for the examined set. The method could, therefore, be classified as data reduction through identification of typical complexes. The principle of the method is as follows: Each pattern is described by a vector (the choice of representation depending upon the particular application). This vector may then be normalized to eliminate, for example, the effect of different scales. Vectors thus obtained are then considered as points in a multidimensional Euclidian space. Distance between points is calculated and compared against a given value which serves as a measure of similarity. Points that are found to be sufficiently close to one another are grouped together into clusters and assigned weights depending upon the number of points and density of the cluster. Clusters with sufficient weight are retained for further processing. Overlapping clusters are partly eliminated according to a criterion described in the text. Patterns associated with the remaining clusters are then used for averaging. Resulting patterns are the desired typical patterns." @default.
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- W2034302609 title "A clustering technique in the classification of almost periodic waveforms" @default.
- W2034302609 doi "https://doi.org/10.1016/0010-4809(72)90042-0" @default.
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