At the intersection of mathematics, engineering, and computer science sits the thriving field of compressive sensing. Based on the premise that data acquisition and compression can be performed simultaneously, compressive sensing finds applications in imaging, signal processing, and many other domains. In the areas of applied mathematics, electrical engineering, and theoretical computer science, an explosion of research activity has already followed the theoretical results that highlighted the efficiency of the basic principles. The elegant ideas behind these principles are also of independent interest to pure mathematicians. A Mathematical Introduction to Compressive Sensing gives a detailed account of the core theory upon which the field is build. With only moderate prerequisites, it is an excellent textbook for graduate courses in mathematics, engineering, and computer science. It also serves as a reliable resource for practitioners and researchers in these disciplines who want to acquire a careful understanding of the subject. A Mathematical Introduction to Compressive Sensing uses a mathematical perspective to present the core of the theory underlying compressive sensing.
The 19th century in France witnessed the emergence of the structures of the modern art market that remain until this day. This book examines the relationship between the avant-garde Barbizon landscape painter, Théodore Rousseau (1812-1867), and this market, exploring the constellation of patrons, art dealers and critics who surrounded the artist. It argues for the pioneering role of Rousseau, his patrons and his public in the origins of the modern art market, and, in so doing, shifts attention away from the more traditional focus on the novel careers of the Impressionists and their supporters. Drawing on extensive archival research, the book provides new insight into the role of the modern artist as professional. It provides a new understanding of the complex iconographical and formal choices within Rousseau's work, rediscovering the original radical charge that once surrounded the artist's work and led to extensive and peculiarly modern tensions with the market place.
The festivals of the Athenian sacred calendar constitute a vital key to classical Greek culture and religion. Erika Simon sets out here to explicate those complex and often obscure festivals. By careful marshaling of a variety of proofs from literary, historical, and archaeological sources, she is able to justify some startling conclusions and achieve a comprehensive and truly original synthesis that clarifies, as never before, the probable origins and meanings of the Attic cults.
Though well-known as the author of Trilby and the creator of Svengali, the writer-artist George Du Maurier had many other accomplishments that are less familiar to modern audiences. This collection traces Du Maurier’s role as a participant in the wider cultural life of his time, restoring him to his proper status as a major Victorian figure. Divided into sections, the volume considers Du Maurier as an artist, illustrator and novelist who helped to form some of the key ideas of his time. The contributors place his life and work in the context of his treatment of Judaism and Jewishness; his fascination with urbanization, Victorian science, technology and clairvoyance; his friendships and influences; and his impact on notions of consumerism and taste. As an illustrator, Du Maurier collaborated with Thomas Hardy, Elizabeth Gaskell and sensational writers such as M. E. Braddon and the author of The Notting Hill Mystery. These partnerships, along with his reflections on the art of illustration, are considered in detail. Impossible to categorize, Du Maurier was an Anglo-Frenchman with cultural linkages in France, England, and America; a social commentator with an interest in The New Woman; a Punch humourist; and a friend of Henry James, with whom he shared a particular interest in the writing of domesticity and domestic settings. Closing with a consideration of Du Maurier’s after-life, notably the treatment of his work in film, this collection highlights his diverse achievements and makes a case for his enduring significance.
This text provides deep and comprehensive coverage of the mathematical background for data science, including machine learning, optimal recovery, compressed sensing, optimization, and neural networks. In the past few decades, heuristic methods adopted by big tech companies have complemented existing scientific disciplines to form the new field of Data Science. This text embarks the readers on an engaging itinerary through the theory supporting the field. Altogether, twenty-seven lecture-length chapters with exercises provide all the details necessary for a solid understanding of key topics in data science. While the book covers standard material on machine learning and optimization, it also includes distinctive presentations of topics such as reproducing kernel Hilbert spaces, spectral clustering, optimal recovery, compressed sensing, group testing, and applications of semidefinite programming. Students and data scientists with less mathematical background will appreciate the appendices that provide more background on some of the more abstract concepts.
At the intersection of mathematics, engineering, and computer science sits the thriving field of compressive sensing. Based on the premise that data acquisition and compression can be performed simultaneously, compressive sensing finds applications in imaging, signal processing, and many other domains. In the areas of applied mathematics, electrical engineering, and theoretical computer science, an explosion of research activity has already followed the theoretical results that highlighted the efficiency of the basic principles. The elegant ideas behind these principles are also of independent interest to pure mathematicians. A Mathematical Introduction to Compressive Sensing gives a detailed account of the core theory upon which the field is build. With only moderate prerequisites, it is an excellent textbook for graduate courses in mathematics, engineering, and computer science. It also serves as a reliable resource for practitioners and researchers in these disciplines who want to acquire a careful understanding of the subject. A Mathematical Introduction to Compressive Sensing uses a mathematical perspective to present the core of the theory underlying compressive sensing.
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