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[null,"1.","Record Nr.",null,"UNINA9910450557103321"]
[null,null,"Autore",null,"Steele J. Michael"]
[null,null,"Titolo",null,"The Cauchy-Schwarz master class : an introduction to the art of mathematical inequalities / / J. Michael Steele [[electronic resource]]"]
[null,null,"Pubbl/distr/stampa",null,"Cambridge : , : Cambridge University Press, , 2004"]
[null,null,"ISBN",null,"1-316-09932-6"]
[{"$nulls":4},"1-107-15043-4"]
[{"$nulls":4},"9786613329264"]
[{"$nulls":4},"0-511-21311-5"]
[{"$nulls":4},"0-511-21134-1"]
[{"$nulls":4},"1-283-32926-3"]
[{"$nulls":4},"0-511-81710-X"]
[{"$nulls":4},"0-511-21492-8"]
[{"$nulls":4},"0-511-21671-8"]
[{"$nulls":4},"0-511-56706-5"]
[null,null,"Descrizione fisica",null,"1 online resource (x, 306 pages) : digital, PDF file(s)"]
[null,null,"Collana",null,"MAA problem books series"]
[null,null,"Disciplina",null,"512.9/7"]
[null,null,"Soggetti",null,"Inequalities (Mathematics)"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Title from publisher's bibliographic system (viewed on 05 Oct 2015)."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references (p. 292-301) and index."]
[null,null,"Nota di contenuto",null,"Cover; Half-title; Series-title; Title; Copyright; Contents; Preface; 1 Starting with Cauchy; 2 Cauchy's Second Inequality: The AM-GM Bound; 3 Lagrange's Identity and Minkowski's Conjecture; 4 On Geometry and Sums of Squares; 5 Consequences of Order; 6 Convexity - The Third Pillar; 7 Integral Intermezzo; 8 The Ladder of Power Means; 9 Hölder's Inequality; 10 Hilbert's Inequality and Compensating Dificulties; 11 Hardy's Inequality and the Flop; 12 Symmetric Sums; 13 Majorization and Schur Convexity; 14 Cancellation and Aggregation; Solutions to the Exercises; Chapter Notes; References; Index"]
[null,null,null,"Sommario/riassunto","This lively, problem-oriented text, first published in 2004, is designed to coach readers toward mastery of the most fundamental mathematical inequalities. With the Cauchy-Schwarz inequality as the initial guide, the reader is led through a sequence of fascinating problems whose solutions are presented as they might have been discovered - either by one of history's famous mathematicians or by the reader. The problems emphasize beauty and surprise, but along the "]
[{"$nulls":4},"way readers will find systematic coverage of the geometry of squares, convexity, the ladder of power means, majorization, Schur convexity, exponential sums, and the inequalities of Hölder, Hilbert, and Hardy. The text is accessible to anyone who knows calculus and who cares about solving problems. It is well suited to self-study, directed study, or as a supplement to courses in analysis, probability, and combinatorics."]
[null,"2.","Record Nr.",null,"UNINA9910811712103321"]
[null,null,"Autore",null,"Rajinikanth Venkatesan"]
[null,null,"Titolo",null,"A beginner's guide to multilevel image thresholding / / Venkatesan Rajinikanth, Nadaradjane Sri Madhava Raja, Nilanjan Dey"]
[null,null,"Pubbl/distr/stampa",null,"Boca Raton, FL : , : CRC Press, , 2021"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"1-00-304944-3"]
[{"$nulls":4},"1-000-22833-9"]
[{"$nulls":4},"1-003-04944-3"]
[{"$nulls":4},"1-000-22845-2"]
[null,null,"Edizione",null,"[First edition]"]
[null,null,"Descrizione fisica",null,"1 online resource : illustrations, portraits (chiefly color)"]
[null,null,"Collana",null,"CRC focus series"]
[{"$nulls":4},"Intelligent signal processing and data analysis"]
[null,null,"Disciplina",null,"006.6"]
[{"$nulls":4},"621.367"]
[null,null,"Soggetti",null,"Image segmentation"]
[{"$nulls":4},"Threshold logic"]
[{"$nulls":4},"Imaging systems in medicine"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,null,"Sommario/riassunto","\"Choosing appropriate thresholding based on the existing image (Grayscale/RGB) and the assigned task is essential to attain better result and the complexity of the image thresholding is largely reduced with the help of a chosen heuristic algorithm technique. This book emphasizes various image thresholding methods that are necessary for image pre-processing and initial level enhancement. It presents a detailed evaluation, such as choosing the threshold function, need for the heuristic algorithm, choice of objective function, and evaluation of the outcome along with real-time applications in detail\"--"]