نتایج جستجو برای: local maxima and minima

تعداد نتایج: 16897595  

ژورنال: :مهندسی نقشه برداری و اطلاعات مکانی 0
امید آئینه o. aieneh سعید صادقیان s. sadeghian

برای استخراج پارامترهای هندسی تک تک درختان در گذشته از دو روش فتوگرامتری و میدانی استفاده می کردند، روش میدانی یعنی استخراج پارامترهای هندسی تک تک درختان به صورت دستی،اما روش میدانی به شدت وقت گیر می باشد همچنین عکسهای هوایی به طور مستقیم نمی توانند اطلاعات ساختار سه بعدی جنگل را تهیه کنند، به همین خاطر تکنولوژی لیدار اخیرا به طور گسترده ای مورد استفاده قرار گرفته است. اولین گام برای استخراج پا...

Journal: :Edinburgh Mathematical Notes 1940

Journal: :SIAM Review 2015
James Bisgard

Variational methods find solutions of equations by considering a solution as a critical point of an appropriately chosen function. Local minima and maxima are well-known types of critical points. We explore methods for finding critical points that are neither local maxima or minima, but instead are mountain passes or saddle points. Criteria for the existence of minima or maxima are well-known, ...

2010
Karen Villaverde Vladik Kreinovich

The problem of locating local maxima and minima of a function from approximate measurement results is vital for many physical applications: in spectral analysis, chemical species are identified by locating local maxima of the spectra; in radioastronomy, sources of celestial radio emission and and their subcomponents are identified by locating local maxima of the measured brightness of the radio...

2004
Zhi-Wei Sun ZHI-WEI SUN

Let h1, · · · , hn be positive integers. We study new sums m(h1, · · · , hn) = h1−1 ∑ r1=0 · · · hn−1 ∑ rn=0 min { r1 h1 , · · · , rn hn } and M(h1, · · · , hn) = h1−1 ∑ r1=0 · · · hn−1 ∑ rn=0 max { r1 h1 , · · · , rn hn } , the first of which times h1 · · ·hn is the number of lattice points in a pyramid of dimension n + 1. We show that m(h1, · · · , hn) (h1 − 1) · · · (hn − 1) = 1 + ∑ ∅6 =I⊆{1...

Journal: :Proceedings of the Edinburgh Mathematical Society 1893

Journal: :Discrete Mathematics 2002

2017
T. Kalaiselvi P. Sriramakrishnan

In this work, we have a proposed an automatic method to brain tumor segmentation using magnetic resonance imaging (MRI) histogram. In our proposed method input is taken from abnormal slice of the MRI volume. Based on image histogram of the abnormal slice, our algorithm automatically detected the local minima and maxima using histogram smoothing techniques. Threshold value obtained from local mi...

Journal: :Int. J. Math. Mathematical Sciences 2005
Lane H. Clark

The extension of permutation statistics to labelled trees is the subject of a number of articles. Generating functions for the number of labelled trees of several types according to the number of ascents and descents are given in [4]. A functional equation satisfied by the generating function for the number of labelled trees according to the number of descents and leaves is given in [5]. Centra...

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