{"product_id":"9781394196777-nr-extensions-alignment-data-rn-c","title":"Near Extensions and Alignment of Data in R(superscript)n","description":"\u003cmeta content=\"text\/html; charset=utf-8\" http-equiv=\"Content-Type\"\u003e\u003cp\u003e\u003cspan\u003eWhitney Extensions of Near Isometries, Shortest Paths, Equidistribution, Clustering and Non-rigid Alignment of data in Euclidean space\u003cbr\u003e\u003cp\u003e\u003cb\u003eNear Extensions and Alignment of Data in R\u003csup\u003en\u003c\/sup\u003e\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eComprehensive resource illustrating the mathematical richness of Whitney Extension Problems, enabling readers to develop new insights, tools, and mathematical techniques\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eNear Extensions and Alignment of Data in R\u003csup\u003en\u003c\/sup\u003e\u003c\/i\u003e demonstrates a range of hitherto unknown connections between current research problems in engineering, mathematics, and data science, exploring the mathematical richness of near Whitney Extension Problems, and presenting a new nexus of applied, pure and computational harmonic analysis, approximation theory, data science, and real algebraic geometry. For example, the book uncovers connections between near Whitney Extension Problems and the problem of alignment of data in Euclidean space, an area of considerable interest in computer vision.\u003c\/p\u003e \u003cp\u003eWritten by a highly qualified author, \u003ci\u003eNear Extensions and Alignment of Data in R\u003csup\u003en\u003c\/sup\u003e\u003c\/i\u003e includes information on:\u003c\/p\u003e \u003cul\u003e\n\u003cli\u003eAreas of mathematics and statistics, such as harmonic analysis, functional analysis, and approximation theory, that have driven significant advances in the field\u003c\/li\u003e\n\u003cli\u003eDevelopment of algorithms to enable the processing and analysis of huge amounts of data and data sets\u003c\/li\u003e\n\u003cli\u003eWhy and how the mathematical underpinning of many current data science tools needs to be better developed to be useful\u003c\/li\u003e\n\u003cli\u003eNew insights, potential tools, and mathematical techniques to solve problems in Whitney extensions, signal processing, shortest paths, clustering, computer vision, optimal transport, manifold learning, minimal energy, and equidistribution\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003eProviding comprehensive coverage of several subjects, \u003ci\u003eNear Extensions and Alignment of Data in R\u003csup\u003en\u003c\/sup\u003e\u003c\/i\u003e is an essential resource for mathematicians, applied mathematicians, and engineers working on problems related to data science, signal processing, computer vision, manifold learning, and optimal transport.\u003c\/p\u003e\n\u003cbr\u003e\u003cbr\u003e\u003c\/span\u003e\u003c\/p\u003e","brand":"Rarewaves","offers":[{"title":"Default Title","offer_id":41110382313569,"sku":"9781394196777","price":122.54,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0092\/7504\/8033\/files\/orig_28180826.jpg?v=1722485133","url":"https:\/\/www.rarewaves.com\/products\/9781394196777-nr-extensions-alignment-data-rn-c","provider":"Rarewaves.com","version":"1.0","type":"link"}