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Space vector modulation (SVM) is an algorithm for the control of pulse-width modulation (PWM), invented by Gerhard Pfaff, Alois Weschta, and Albert Wick in 1982. [ 1 ] [ 2 ] It is used for the creation of alternating current (AC) waveforms ; most commonly to drive 3 phase AC powered motors at varying speeds from DC using multiple class-D ...
The copy of the Gutenberg Bible held at the Bibliothèque nationale de France. The Gutenberg Bible, also known as the 42-line Bible, the Mazarin Bible or the B42, was the earliest major book printed in Europe using mass-produced metal movable type. It marked the start of the "Gutenberg Revolution" and the age of printed books in the West.
Back in the 1450s, when the Bible became the first major work printed in Europe with moveable metal type, Johannes Gutenberg was a man with a plan. The German inventor decided to make the most of ...
The hyperplane learned in feature space by an SVM is an ellipse in the input space. In machine learning , the polynomial kernel is a kernel function commonly used with support vector machines (SVMs) and other kernelized models, that represents the similarity of vectors (training samples) in a feature space over polynomials of the original ...
Working for Fust, Schöffer was the principal workman of Johannes Gutenberg, inventor of modern typography, whose 42-Line Bible was completed in 1455. In 1455 he testified for Johann Fust against Gutenberg. [2] By 1457, he and Fust had formed the firm Fust and Schöffer, after the foreclosure of the mortgage on Gutenberg's printing workshop. [3]
Recto page from a rare Blackletter Bible (1497). The canons of page construction are historical reconstructions, based on careful measurement of extant books and what is known of the mathematics and engineering methods of the time, of manuscript-framework methods that may have been used in Medieval- or Renaissance-era book design to divide a page into pleasing proportions.
Sequential minimal optimization (SMO) is an algorithm for solving the quadratic programming (QP) problem that arises during the training of support-vector machines (SVM). It was invented by John Platt in 1998 at Microsoft Research. [1] SMO is widely used for training support vector machines and is implemented by the popular LIBSVM tool.