Titlebook: Approximation of Euclidean Metric by Digital Distances; Jayanta Mukhopadhyay Book 2020 The Author(s), under exclusive license to Springer

mountebank

書目名稱Approximation of Euclidean Metric by Digital Distances影響因子(影響力)




書目名稱Approximation of Euclidean Metric by Digital Distances影響因子(影響力)學(xué)科排名




書目名稱Approximation of Euclidean Metric by Digital Distances網(wǎng)絡(luò)公開度




書目名稱Approximation of Euclidean Metric by Digital Distances網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Approximation of Euclidean Metric by Digital Distances被引頻次




書目名稱Approximation of Euclidean Metric by Digital Distances被引頻次學(xué)科排名




書目名稱Approximation of Euclidean Metric by Digital Distances年度引用




書目名稱Approximation of Euclidean Metric by Digital Distances年度引用學(xué)科排名




書目名稱Approximation of Euclidean Metric by Digital Distances讀者反饋




書目名稱Approximation of Euclidean Metric by Digital Distances讀者反饋學(xué)科排名

Permanent

cauda-equina

Linear Combination of Digital Distances,derestimated and overestimated norms. In particular, it presents an analysis on approximation of Euclidean metrics by a linear combination of weighted .-cost and chamfering weighted distance functions. The same theory is applied to get new results and insights in the approximation of Euclidean metri

過度

Book 2020. It discusses the properties of these distance functions and presents various kinds of error analysis in approximating Euclidean metrics. It also presents a historical perspective on efforts and motivation for approximating Euclidean metrics by digital distances from the mid-sixties of the previous

參考書目

五行打油詩

y of digital distances.Summarizes properties of different cl.This book discusses different types of distance functions defined in an n-D integral space for their usefulness in approximating the Euclidean metric. It discusses the properties of these distance functions and presents various kinds of er

Ophthalmologist

ethnology

工作

Jargon

Linear Combination of Digital Distances, .-cost and chamfering weighted distance functions. The same theory is applied to get new results and insights in the approximation of Euclidean metrics by other sub-classes such as m-neighbor, t-cost, weighted t-cost, and hyperoctagonal distances.