Titlebook: Network Science; 7th International Wi Pedro Ribeiro,Fernando Silva,Rosário Laureano Conference proceedings 2022 Springer Nature Switzerland

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,Competitive Information Spreading on Modular Networks,ture has a strong effect on not only the spreading process but also the final prevalence. Specifically, two competing pieces of information cannot coexist and one drives out the other on a non-modular network, whereas they can coexist in different communities on a modular network. Our results sugges

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Ivana Bachmann,Javier Bustos-Jiméneztained and should be accessible to graduate students in analysis.The core of the book is composed of regularity results that were proved in the last ten years and which are presented in a more detailed and unified way..978-3-7643-7302-3Series ISSN 0743-1643 Series E-ISSN 2296-505X

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Rouzbeh Hasheminezhad,Ulrik Brandesis appropriate for researchers, upper level students (masters level and beyond) and practitioners wishing to revive their knowledge of times series analysis or to quickly learn about the main mechanisms of SSA.  .                          .            .978-1-137-40951-5Series ISSN 2662-639X Series E-ISSN 2662-6403

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Satoshi Furutani,Toshiki Shibahara,Mitsuaki Akiyama,Masaki Aidans and econometricians, specialists in any discipline in which problems of time series analysis and forecasting occur, specialists in signal processing and those needed to extract signals from noisy data, and students taking courses on applied time series analysis.978-3-642-34913-3Series ISSN 2191-544X Series E-ISSN 2191-5458

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Sofia Dokuka,Elizaveta Sivak,Ivan Smirnovby Fraedrich (1986) and Broomhead and King (l986a). Prior to this, SSA was used in biological oceanography by Colebrook (1978). In the digi­ tal signal processing community, the approach is also known as the Karhunen-Loeve (K-L) expansion (Pike et aI., 1984). Like other techniques based on spectral decomposit978-1-4419-3266-2978-1-4757-2514-8