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We report Lobachevsky University Database (LUDB) of ECG signals, an open tool for validating ECG delineation algorithms, that is superior to the existing publicly available data bases in several aspects. LUDB contains 200 recordings of 10-second 12-lead electrocardiograms (ECG) from different subjects, representative of a variety of signal morfologies. The boundaries and peaks of QRS complexes and P and T waves are manually annotated by cardiologists for all recordings and independently for each lead, and all records received an expert classification by abnormalities. We present a case study for the recently proposed wavelet-based algorithm and the broadly used ecg-kit tool, and demonstrate the advantage of multi-lead ECG data analysis. LUDB contributes to the diversity of public databases employed in developing and validating novel ECG analysis algorithms, including the most advanced based on deep learning neural networks.

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‫ޒ‬ d : Ax ≥ b} can be found by solving a similar problem for the cone {(x, x d + 1 ) ∈ ‫ޒ‬ d + 1: Ax -bx d + 1 ≥ 0, x d + 1 ≥ 0} and, then, setting x d + 1 = 1.These problems arise in many applications, such as computer graphics, physical simulation, image processing, cartography, computational biology, theoretical physicist, and others. The construction of a Abstract-A new modification of the double description method is proposed for constructing the skel eton of a polyhedral cone. Theoretical results and a numerical experiment show that the modification is considerably superior to the original algorithm in terms of speed.