convexity of function 中文意思是什麼

convexity of function 解釋
函數的凸性
  • convexity : n. 凸度;凸狀;凸面(體)。
  • of : OF =Old French 古法語。
  • function : n 1 功能,官能,機能,作用。2 〈常 pl 〉職務,職責。3 慶祝儀式;(盛大的)集會,宴會。4 【數學】...
  1. Geometric convexity of gamma function

    函數的幾何凸性
  2. In the higher mathematics category, routine methods to work out the proof of an inequation are a flexible use of mathematical knowledge like monotonicity of functions, extremum values, maximum and minimum values, convexity function, medium value theorem, taylor equation, holder inequation, schwarz inequation, and the analysis, formation and transformation of inequation problems as well

    摘要在高等數學?疇中,靈活運用函數的單調性、極值、最值、凸性函數、以及中值定理與泰勒公式、赫爾德不等式、施瓦茲不等式等數學知識,對不等式問題進行分析、構造與轉化,是解決不等式的證明問題的常用方法。
  3. First according to the fact that tangential components of the evolution do not affect the geometric shape of the evolving curves, we introduce the evolution equation of geometric quantities for the general planar curves. then we describe the work of gage - hamilton briefly. last we consider a special curvature flow of curve which evolves with speed function of the principal curvatures along the inner norm and show that convexity of the curve is kept and its length and area are contracted if the initial closed curve is smooth and convex. so the final shape of the curve will be a point in finite time

    首先根據曲線在切向分量上發展是不影響曲線的發展形狀,我們引入了曲線的一些幾何變量的發展方程;其次我們簡要地回顧gage - hamilton研究曲線發展的一般步驟;最後我們考慮沿曲線的內法線以曲率的函數為發展速度的一類特殊的曲線族,證明了在初始曲線為凸的閉平面簡單曲線條件下,曲線將保持凸的,並且它的面積和周長將同時收縮,並在有限時間內成為一個點。
  4. The research methods are : using the conditional probability theory to work out the moment generating function of process s ( t ) and its distribution function ; using the increasing and declining character and the convexity to compare the lundberg exponent and the ruin probability of different processes

    研究方法為:利用條件概率證明過程s ( t )的矩母函數以及其分佈函數;利用增減性以及凹凸性比較lundberg指數,從而比較其相關性對破產概率的影響。
  5. This property is independent with the convexity of the objective function and the line search used. therefore, the generated directions are descent directions of the objective function

    這一個性質與目標函數的凸性以及線性搜索無關,因而,產生的搜索方向總是目標函數的下降方向。
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