Selling Earth observation satellites on their abilities to predict and limit adverse environmental change, politicians, business leaders, the media, and technology enthusiasts have spent sixty years arguing that space exploration can create a more peaceful, prosperous world. Capitalist states have also socialized the risk and privatized the profits of the commercial space industry by convincing taxpayers to fund surveillance technologies as necessary components of sovereignty, freedom, and democracy. Jocelyn Wills's Tug of War reminds us that colonizing the cosmos has not only accelerated the arms race but also encouraged government contractors to compete for the military and commercial spoils of surveillance. Although Canadians prefer to celebrate their role as purveyors of peaceful space applications, Canada has played a pivotal part in the expansion of neoliberal policies and surveillance networks that now encircle the globe, primarily as a political ally of the United States and component supplier for its military-industrial complex. Tracing the forty-five-year history of Canada's largest space company - MacDonald, Dettwiler and Associates (MDA) - through the lens of surveillance studies and a trove of oral history transcripts, government documents, trade journals, and other sources, Wills places capitalism's imperial ambitions squarely at the centre of Canada-US relations and the privatization of the Canadian political economy. --Dust jacket.
"Lefebvre, Love and Struggle provides the only comprehensive guide to Lefebvre's work. It is an accessible introduction to one of the most significant European thinkers of the twentieth century. Rob Shields draws on the full range of Lefebvres writings, including many previously untranslated and unpublished works and correspondence. Topics covered include Lefebvre's early relationship with Marxism, his critique of the rise of fascism, as well as his Critique of Everyday Life and the significant work on urban space for which he is best known today."--Book cover.
"Interference Avoidance Methods for Wireless Systems is an introduction to wireless techniques useful for uncoordinated unlicensed band systems, which use adaptive transmitters and receivers. The book provides a comprehensive theoretical analysis of interference avoidance algorithms in a general signal space framework that applies to a wide range of wireless communication scenarios with multiple users accessing the same communication resources." "This book will be of interest to researchers, graduate students, and engineers working in the area of wireless communications as well as to technology policy makers working on radio frequency spectrum allocation. The book can also be used as a supplement text to advanced topics graduate courses in the area of wireless communication systems."--BOOK JACKET.
The past decade has seen considerable theoretical and applied research on Markov decision processes, as well as the growing use of these models in ecology, economics, communications engineering, and other fields where outcomes are uncertain and sequential decision-making processes are needed. A timely response to this increased activity, Martin L. Puterman's new work provides a uniquely up-to-date, unified, and rigorous treatment of the theoretical, computational, and applied research on Markov decision process models. It discusses all major research directions in the field, highlights many significant applications of Markov decision processes models, and explores numerous important topics that have previously been neglected or given cursory coverage in the literature. Markov Decision Processes focuses primarily on infinite horizon discrete time models and models with discrete time spaces while also examining models with arbitrary state spaces, finite horizon models, and continuous-time discrete state models. The book is organized around optimality criteria, using a common framework centered on the optimality (Bellman) equation for presenting results. The results are presented in a "theorem-proof" format and elaborated on through both discussion and examples, including results that are not available in any other book. A two-state Markov decision process model, presented in Chapter 3, is analyzed repeatedly throughout the book and demonstrates many results and algorithms. Markov Decision Processes covers recent research advances in such areas as countable state space models with average reward criterion, constrained models, and models with risk sensitive optimality criteria. It also explores several topics that have received little or no attention in other books, including modified policy iteration, multichain models with average reward criterion, and sensitive optimality. In addition, a Bibliographic Remarks section in each chapter comments on relevant historical references in the book's extensive, up-to-date bibliography...numerous figures illustrate examples, algorithms, results, and computations...a biographical sketch highlights the life and work of A. A. Markov...an afterword discusses partially observed models and other key topics...and appendices examine Markov chains, normed linear spaces, semi-continuous functions, and linear programming. Markov Decision Processes will prove to be invaluable to researchers in operations research, management science, and control theory. Its applied emphasis will serve the needs of researchers in communications and control engineering, economics, statistics, mathematics, computer science, and mathematical ecology. Moreover, its conceptual development from simple to complex models, numerous applications in text and problems, and background coverage of relevant mathematics will make it a highly useful textbook in courses on dynamic programming and stochastic control.
This book is concerned with the analysis of multivariate time series data. Such data might arise in business and economics, engineering, geophysical sciences, agriculture, and many other fields. The emphasis is on providing an account of the basic concepts and methods which are useful in analyzing such data, and includes a wide variety of examples drawn from many fields of application. The book presupposes a familiarity with univariate time series as might be gained from one semester of a graduate course, but it is otherwise self-contained. It covers the basic topics such as autocovariance matrices of stationary processes, vector ARMA models and their properties, forecasting ARMA processes, least squares and maximum likelihood estimation techniques for vector AR and ARMA models. In addition, it presents some more advanced topics and techniques including reduced rank structure, structural indices, scalar component models, canonical correlation analyses for vector time series, multivariate nonstationary unit root models and co-integration structure and state-space models and Kalman filtering techniques.
Tug of war by Jocelyn Wills | Literally Just Books
