Sample recognition questions

The successful appHcation of pattern recognition methods depends on a number of assumptions (14). Obviously, there must be multiple samples from a system with multiple measurements consistendy made on each sample. For many techniques the system should be overdeterrnined the ratio of number of samples to number of measurements should be at least three. These techniques assume that the nearness of points in hyperspace faithfully redects the similarity of the properties of the samples. The data should be arranged in a data matrix with one row per sample, and the entries of each row should be the measurements made on the sample, as shown in Figure 1. The information needed to answer the questions must be implicitly contained in that data matrix, and the data representation must be conformable with the pattern recognition algorithms used. 

Since texture has a great deal to do with visual perception, it is interesting to discuss some work done on texture recognition. The first question we want to focus on is what makes two samples with identical overall concentration exhibit different textures Perfect gross uniformity implies identical concentration in all samples. Julesz (68), in an interesting... 

The racemic mixture of all four components LP2, LU2, DP2, and DU2 yielded long superhelices of opposite handedness that coexisted in the same sample, pointing to the occurrence of spontaneous resolution through chiral selection in molecular recognition-directed self-assembly of supramolecular liquid-crystalline polymers. Such chiral selection features of self-organized entities are of general significance in connection with the questions of spontaneous resolution and of chirality amplification. This was confirmed by subsequent studies on a variety of helical supramolecular polymers (see Chapters 2, 3, and 6). 

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