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Titlebook: Robuste Unternehmen; Krisenfest in Zeiten Frank Weber,Joachim Berendt Book 2017 Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer N

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From HMMS to Segment Models: Stochastic Modeling for CSR,y be classified as segment models. This chapter describes a general probabilistic framework for segment models, including HMMs as a special case, giving options for modeling assumptions in terms of correlation structure and parameter tying and outlining the extensions to HMM recognition and training algorithms needed to handle segment models.
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Datenauswertung,chprobe gewinnen. Dagegen dient die induktive Statistik, die so genannte Inferenzstatistik, der Verallgemeinerung der Befunde. Mit ihrer Hilfe versucht man, die aus der Stichprobe gewonnenen Erkenntnisse auf einen größeren Bereich, die so genannte Grundgesamtheit oder Population, zu generalisieren.
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https://doi.org/10.1007/978-3-658-03658-4on of multiple dependent measures. The simulation tool was designed to be adaptable to allow continued research on a variety of factors related to the control of autonomous vehicles. A research study using this simulation tool investigated the effects of automation and the number of UCAVs being cont
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Karla Barrantes Chavesith very good results in terms of its ability to decompose the matrices. It has been shown that OnPLS affords a reduced number of globally joint components and increased intercorrelations of scores, and that it greatly facilitates interpretation of the models. Preliminary results in the application
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nd Windows Phone apps using C# and .NET. This book explains .Xamarin Mobile Application Development is a hands-on Xamarin.Forms primer and a cross-platform reference for building native Android, iOS, and Windows Phone apps using C# and .NET. This book explains how to use Xamarin.Forms, Xamarin.Andro
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0302-9743 of the world‘s most prominent neural network researchers. These tricks can make a substantial difference (in terms of speed, ease of implementation, and accuracy) when it comes to putting algorithms to work on real problems..978-3-642-35288-1978-3-642-35289-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
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