漸進分習法 的英文怎麼說
中文拼音 [jiānjìnfēnxífǎ]
漸進分習法
英文
progressive part method-
On the ground of educative theory, this paper exposits connotation and characteristic of project - based learning and why we should also enforce project - based learning in high school. as far as substance of project - based learning and objective circumstance what it should have are concerned, it points out the practical ability. at last, based on that university physics education has relatively longer cycle, it proposes stage pattern for enforce project - based learning and give two concrete cases, which discuss capacitance of confocal oval - shaped stylar capacitor and potential distribution of charged conductor of surface being uniparted hyperboloid
本文在具體的教育理論指導下，闡述了研究性學習的內涵及特點；在大學物理中實施研究性學習的意義；以及就研究性學習的實質和所需具備的客觀條件而言，論述了研究性學習在高校中實施的可行性；並根據大學物理教育具有周期性相對較長和專業循序漸進的特點，提出了研究性學習的階段性模式，並給出了具體的實例，利用保角變換法討論了共焦橢圓柱形電容器電容及單葉雙曲面帶電導體的電位分佈。Furthermore, utilizing the characteristic that filtering error covariance expresses filtering precision and the principle of information conservation, the dynamic and reasonable distribution of distributed tracks weight coefficient is accomplished. jerk model and strong tracking filter is organically assembled, and based on spatio - temporal synthetically analysis and lme, a self - learning estimation method of the system measurement variance is given. the method improves obviously the
3 、將jerk模型與強跟蹤濾波演算法有機地結合，並利用時空綜合分析和極大似然估計的思想推導出了一種系統量測方差自學習修正方法，以優化強跟蹤濾波演算法中次優漸消因子和濾波增益的在線選擇，同時根據多傳感器數據融合具有改善濾波精度的性質，進而給出一種基於jerk模型的多傳感器數據融合演算法。For weight setting, first briefly introduces a known weight learning arithmetic based on rough set, and carrying through problem analysis and improvement, also introduces a weight vector gradually learning arithmetic, when user is n ' t satisfied with current weights, we can use it to revise weights gradually
對于權重設置，先簡要介紹了已有的一種基於粗糙集的權重自動學習演算法，並對其進行了問題分析和改進，還介紹了一種權向量漸進學習演算法，當用戶對當前權值不滿意時，可採用此演算法進行逐步修正。Unlike approach theory in orthodox statistics, statistical learning theory especially studies the law of machine learning when samples are finite. it has proved the bound of actual risk is made up of experiential risk and belief bound. vc dimension is used to control generation ability ; structural risk minimization induce principle is used to control the bound on the value of achieved risk by controlling experiential risk and belief bound at the same time
不同於傳統統計學的漸進理論，統計學習專門研究有限樣本情況下的機器學習規律，它從理論上證明了實際風險的界是由經驗風險和置信范圍兩部分構成的，並給出了控制置信范圍的方法vc維。分享友人