Exploring the interrelations between generalized metric spaces, lattice-ordered groups, and order statistics, the book contains a new algebraic approach to Signal Processing Theory. It describes mathematical concepts and results important in the development, analysis, and optimization of signal processing algorithms intended for various applications. The book offers a solution of large-scale Signal Processing Theory problems of increasing both signal processing efficiency under prior uncertainty conditions and signal processing rate that is provided by multiplication-free signal processing algorithms based on lattice-ordered group operations. From simple basic relationships to computer simulation, the text covers a wide range of new mathematical techniques essential for understanding the proposed signal processing algorithms developed for solving the following problems: signal parameter and spectral estimation, signal filtering, detection, classification, and resolution; array signal processing; demultiplexing and demodulation in multi-channel communication systems and multi-station networks; wavelet analysis of 1D/ 2D signals. Along with discussing mathematical aspects, each chapter presents examples illustrating operation of signal processing algorithms developed for various applications. The book helps readers understand relations between known classic and obtained results as well as recent research trends in Signal Processing Theory and its applications, providing all necessary mathematical background concerning lattice-ordered groups to prepare readers for independent work in the marked directions including more advanced research and development.
Exploring the interrelation between information theory and signal processing theory, the book contains a new algebraic approach to signal processing theory. Readers will learn this new approach to constructing the unified mathematical fundamentals of both information theory and signal processing theory in addition to new methods of evaluating quality indices of signal processing. The book discusses the methodology of synthesis and analysis of signal processing algorithms providing qualitative increase of signal processing efficiency under parametric and nonparametric prior uncertainty conditions. Examples are included throughout the book to further emphasize new material.
Exploring the interrelations between generalized metric spaces, lattice-ordered groups, and order statistics, the book contains a new algebraic approach to Signal Processing Theory. It describes mathematical concepts and results important in the development, analysis, and optimization of signal processing algorithms intended for various applications. The book offers a solution of large-scale Signal Processing Theory problems of increasing both signal processing efficiency under prior uncertainty conditions and signal processing rate that is provided by multiplication-free signal processing algorithms based on lattice-ordered group operations. From simple basic relationships to computer simulation, the text covers a wide range of new mathematical techniques essential for understanding the proposed signal processing algorithms developed for solving the following problems: signal parameter and spectral estimation, signal filtering, detection, classification, and resolution; array signal processing; demultiplexing and demodulation in multi-channel communication systems and multi-station networks; wavelet analysis of 1D/ 2D signals. Along with discussing mathematical aspects, each chapter presents examples illustrating operation of signal processing algorithms developed for various applications. The book helps readers understand relations between known classic and obtained results as well as recent research trends in Signal Processing Theory and its applications, providing all necessary mathematical background concerning lattice-ordered groups to prepare readers for independent work in the marked directions including more advanced research and development.
Exploring the interrelation between information theory and signal processing theory, the book contains a new algebraic approach to signal processing theory. Readers will learn this new approach to constructing the unified mathematical fundamentals of both information theory and signal processing theory in addition to new methods of evaluating quality indices of signal processing. The book discusses the methodology of synthesis and analysis of signal processing algorithms providing qualitative increase of signal processing efficiency under parametric and nonparametric prior uncertainty conditions. Examples are included throughout the book to further emphasize new material.
Andrej Zubov byl v roce 2022 nucen opustit svoji rodnou zemi a přijal pozvání rektora Masarykovy univerzity, aby přednášel v Brně. Soubor jeho přednášek česky souhrnně nazvaný „Ruská katastrofa a možnosti, jak ji překonat“ nyní vychází knižně. Autor skrze studium ruských dějin hledá odpovědi na dvě úzce související otázky: Proč bylo Rusko od bolševického převratu po celé dvacáté století neustálým zdrojem agrese? a Existuje nějaká naděje, že se Rusko radikálně promění, přestane být agresorem a stane se mírumilovným státem, demokratickou zemí, jako země EU a NATO? Profesor Zubov věří, že jeho texty přispějí k lepšímu pochopení tragického osudu jeho lidu v minulých i současných staletích, procesů, které vedly k válce, a tím i k budování trvalejšího míru po jejím skončení.
In this book, Makarychev and Medvedev examine the importance of biopolitics in fueling Russia’s confrontation with the West. In their view, the development of Putin’s illiberal authoritarianism was largely triggered by what they call a biopolitical turn. This shift is exemplified by the use of an increasing number of regulatory mechanisms to discipline and constrain the human body. Such political practices concern issues of sexuality, reproductive behavior, adoption, fertility, family planning, public hygiene, and demography. This turn created a new disciplinary framework for the population and the elite. Bans and restrictions of a biopolitical nature, became one of the main tools for articulating the rules of belonging in the political community and drawing its political boundaries. Biopolitical discourses have taken up the core of the Russian identity formation, which contrasts a positive “conservative Russia” with a supposedly vicious “liberal West.” The presentation of the political genealogy of the body-centric structures of power and hegemony in Russia implies their transformation from bio- to necropolitics. Necropolitical (repressive and life-depriving) components are inscribed in the biopolitical regimes of power: they form the core of Putin’s rule over Russia and are a key factor behind the war against Ukraine.
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