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Gangsters and Other Statesmen
How global organized crime shapes the politics of borders in modern conflicts Separatism has been on the rise across the world since the end of the Cold War, dividing countries through political strife, ethnic conflict, and civil war, and redrawing the political map. Gangsters and Other Statesmen examines the role transnational mafias play in the success and failure of separatist movements, challenging conventional wisdom about the interrelation of organized crime with peacebuilding, nationalism, and state making. Danilo Mandić conducted fieldwork in the disputed territories of Kosovo and South Ossetia, talking to mobsters, separatists, and policymakers in war zones and along major smugglin...
Signal Processing Techniques for Knowledge Extraction and Information Fusion
This book brings together the latest research achievements from signal processing and related disciplines, consolidating existing and proposed directions in DSP-based knowledge extraction and information fusion. The book includes contributions presenting both novel algorithms and existing applications, emphasizing on-line processing of real-world data. Readers discover applications that solve biomedical, industrial, and environmental problems.
Complex Valued Nonlinear Adaptive Filters
This book was written in response to the growing demand for a text that provides a unified treatment of linear and nonlinear complex valued adaptive filters, and methods for the processing of general complex signals (circular and noncircular). It brings together adaptive filtering algorithms for feedforward (transversal) and feedback architectures and the recent developments in the statistics of complex variable, under the powerful frameworks of CR (Wirtinger) calculus and augmented complex statistics. This offers a number of theoretical performance gains, which is illustrated on both stochastic gradient algorithms, such as the augmented complex least mean square (ACLMS), and those based on Kalman filters. This work is supported by a number of simulations using synthetic and real world data, including the noncircular and intermittent radar and wind signals.
Recurrent Neural Networks for Prediction
Neural networks consist of interconnected groups of neurons which function as processing units. Through the application of neural networks, the capabilities of conventional digital signal processing techniques can be significantly enhanced.
Data Analytics on Graphs
Aimed at readers with a good grasp of the fundamentals of data analytics, this book sets out the fundamentals of graph theory and the emerging mathematical techniques for the analysis of a wide range of data acquired on graph environments. This book will be a useful friend and a helpful companion to all involved in data gathering and analysis.
Recurrent Neural Networks for Prediction
Durch die Anwendung rückbezüglicher neuronaler Netze läßt sich die Leistungsfähigkeit konventioneller Technologien der digitalen Datenverarbeitung signifikant erhöhen. Von besonderer Bedeutung ist dies für komplexe Aufgaben, wie z.B. die mobile Kommunikation, die Robotik und die Medizintechnik. Das Buch faßt Originalarbeiten zur Stabilität neuronaler Netze zusammen und verbindet streng mathematische Analysen mit anschaulichen Anwendungen und experimentellen Belegen.
Changing Youth Values in Southeast Europe
What shapes the cultural, political and ideological values of young people living in Southeastern Europe? Which identities matter to them? How are their values changing, and how can they be changed? Who is changing them? Europe’s periphery is the testing ground for the success of European values and identities. The future stability and political coherence of the Union will be determined in large measure by identity issues in this region. This book examines the ways in which ethnic and national values and identities have been surpassed as the overriding focus in the lives of the region’s youth. Employing bottom-up, ethnographic, and interview-based approaches, it explores when and where e...
SEE.
Vision traditionally occupies the height of the sensorial hierarchy. The sense of clarity and purity conveyed by vision, allows it to be explicitly associated with truth and knowledge. The law has always relied on vision and representation, from eye-witnesses to photography, to imagery and emblems. The law and its normative gaze can be understood as that which decrees what is permitted to be and become visible and what is not. Indeed, even if law's perspectival view is bound to be betrayed by the realities of perception, it is nonetheless productive of real effects on the world. This first title in the interdisciplinary series 'Law and the Senses' asks how we can develop new theoretical approaches to law and seeing that go beyond a simple critique of the legal pretension to truth. This volume aims to understand how law might see and unsee, and how in its turn is seen and unseen. It explores devices and practices of visibility, the evolution of iconology and iconography, and the relation between the gaze of the law and the blindness of justice. The contributions, all radically interdisciplinary, are drawn from photography, legal theory, philosophy, and poetry.
Advanced Data Analytics for Power Systems
Experts in data analytics and power engineering present techniques addressing the needs of modern power systems, covering theory and applications related to power system reliability, efficiency, and security. With topics spanning large-scale and distributed optimization, statistical learning, big data analytics, graph theory, and game theory, this is an essential resource for graduate students and researchers in academia and industry with backgrounds in power systems engineering, applied mathematics, and computer science.
Recent Trends in Learning From Data
This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research.
