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The object of the study are neural networks. The goal is to understand and develop a recognition system of mathematical formulas and symbols. The article deals with the basic provisions of neural networks, which principle of work is based on functioning neural networks of the human brain. We describe a mathematical representation of the pulse passing through the synaptic connections of neurons and...
A three-dimensional extension of a previously developed metric termed cluster resolution is presented. The cluster resolution metric considers confidence ellipses (here three-dimensional confidence ellipsoids) around clusters of points in principal component or latent variable space. Cluster resolution is defined as the maximum confidence limit at which confidence ellipses do not overlap and can serve...
Direct chemometric interpretation of raw chromatographic data (as opposed to integrated peak tables) has been shown to be advantageous in many circumstances. However, this approach presents two significant challenges: data alignment and feature selection. In order to interpret the data, the time axes must be precisely aligned so that the signal from each analyte is recorded at the same coordinates...
A novel metric termed cluster resolution is presented. This metric compares the separation of clusters of data points while simultaneously considering the shapes of the clusters and their relative orientations. Using cluster resolution in conjunction with an objective variable ranking metric allows for fully automated feature selection for the construction of chemometric models. The metric is based...
The traditional method of percutaneous renal access requires freehand needle placement guided by C-arm fluoroscopy, ultrasonography, or computerized tomography. This approach provides limited objective means for verifying successful access. We developed an impedance based percutaneous Smart Needle system and successfully used it to confirm collecting system access in ex vivo porcine kidneys. The...
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