linear optimization造句
例句與造句
- Design and implementation of linear optimization solving system
大規(guī)模線性優(yōu)化求解系統(tǒng)的設(shè)計(jì)與實(shí)現(xiàn) - Based on theory of convex cones , our extensions of robust linear optimization are done in three directions
摘要本文基于凸錐理論對(duì)魯棒線性最優(yōu)化作了若干拓展。 - The video - based 3d body tracking method under the non - linear optimization framework was proposed , which combined multiple cues and motion prior efficiently
其算法特點(diǎn)是，多種圖像特征和運(yùn)動(dòng)知識(shí)有機(jī)地集成于一個(gè)基于非線性優(yōu)化策略的跟蹤框架中。 - Read sections 7 . 1 - 7 . 3 of chapter 7 . we will cover the basics of linear optimization , including formulations , key concepts , and graphical solution methods
閱讀第七章7 . 1到7 . 3的部份。我們的課程將介紹線性最佳化的基礎(chǔ)，包括方程式，重要概念以及圖形解方法。 - A comprehensive set of lecture notes , from basic principles , such as linear optimization , to sophisticated real - world applications are available . also , there are problem sets in pdf format
本課程提供詳盡的課堂講稿，涵蓋線性規(guī)劃等基本原理以及復(fù)雜的實(shí)際問(wèn)題應(yīng)用。同時(shí)，本課還有一些問(wèn)題集（ pdf格式） 。 - It's difficult to find linear optimization in a sentence. 用linear optimization造句挺難的
- Especially , a kind of non - linear optimization analytic hierarchy process ( ahp ) with experts reliability on the basis of the traditional ahp is proposed , and it is a new method for determining the evaluation indexes weights
特別地，文中在確定評(píng)價(jià)指標(biāo)的權(quán)重時(shí)，在傳統(tǒng)的層次分析法基礎(chǔ)上進(jìn)行改進(jìn)提出了一種新方法帶有專家可信度的非線性優(yōu)化層次分析法。 - Traditional method can be classified two class : linear optimization technique and nonlinear optimization technique , linear optimization technique base on born approximation or rytov approximation is usually used to solve weak scattering problem
線性優(yōu)化方法采用線性近似忽略了散射體內(nèi)部的多次散射，可以有效的反演低對(duì)比度的問(wèn)題，但對(duì)于高對(duì)比度問(wèn)題的求解則有可能不收斂。 - By using rac ( radial alignment constraint ) of imaging process to decompose camera parameters and organizing the solving sequence of the parameters rationally , all parameters can be obtained through solving linear equations that avoid non - linear optimization
巧妙地利用成像過(guò)程中的徑向約束（ rac ）分解攝像機(jī)參數(shù)，使得求解線性方程組即可得到全部的攝像機(jī)參數(shù)，避免非線性優(yōu)化搜索。 - Compared with csm , two examples proved that ann could be trained successfully , even if the available data were insufficient and irregular , while csm showed the limit in selecting model type and non - linear optimization
兩個(gè)實(shí)例的應(yīng)用結(jié)果表明:人工神經(jīng)網(wǎng)絡(luò)通過(guò)神經(jīng)原作用函數(shù)的簡(jiǎn)單復(fù)合就能逼近有限子集的任意非線性函數(shù)，而傳統(tǒng)的統(tǒng)計(jì)方法則存在著如何選擇模型形式及非線性優(yōu)化問(wèn)題，表現(xiàn)出明顯的局限性，并且統(tǒng)計(jì)模型的更新工作相當(dāng)繁重。 - With analogizing the evolution process of atomic transition from excited states to ground state , we proposed a novel non - linear optimization algorithm for geophysical inverse problem , called as simulated atomic transition algorithm ( sata )
在此基礎(chǔ)上，模擬了物理學(xué)中原子從激發(fā)態(tài)向基態(tài)躍遷的物理過(guò)程，建立了一種與原子躍遷過(guò)程相對(duì)應(yīng)的非線性隨機(jī)躍遷數(shù)學(xué)模型和模型解躍遷搜索準(zhǔn)則，導(dǎo)出了適用于一般地球物理資料的模擬原子躍遷的非線性反演算法。 - 2 . on the base of detailedly analysing the fourier neural networks , we find this neural networks have the characteristic which can transform the nonlinear mapping into linear mapping . so , we improve the original learning algorithm based on nonlinear optimization and propose a novel learning algorithm based on linear optimization ( this dissertation adopts the least squares method ) . the novel learning algorithm highly improve convergence speed and avoid local minima problem . because of adopting the least squares method , when the training output samples were affected by white noise , this algorithm have good denoising function
在詳細(xì)分析已有的傅立葉神經(jīng)網(wǎng)絡(luò)的基礎(chǔ)上，發(fā)現(xiàn)傅立葉神經(jīng)網(wǎng)絡(luò)具有將非線性映射轉(zhuǎn)化成線性映射的特點(diǎn)，基于這個(gè)特點(diǎn)，對(duì)該神經(jīng)網(wǎng)絡(luò)原有的基于非線性優(yōu)化的學(xué)習(xí)算法進(jìn)行了改進(jìn)，提出了基于線性優(yōu)化方法(本文采用最小二乘法)的學(xué)習(xí)算法，大大提高了神經(jīng)網(wǎng)絡(luò)的收斂速度并避免了局部極小問(wèn)題；由于采用了最小二乘方法，當(dāng)用來(lái)訓(xùn)練傅立葉神經(jīng)網(wǎng)絡(luò)的訓(xùn)練輸出樣本受白噪聲影響時(shí)，本學(xué)習(xí)算法具有良好的降低噪聲影響的功能。 - We use rac ( radial alignment constraint ) of imaging process to decompose camera parameters . by organizing the solving sequence of the parameters rationally , we can obtain all parameters through solving systems of linear - 3 - abstract equations . accordingly we have changed the situation that ? he former camera calibration rac methods should depend on the non - linear optimization and has strict requirement to illumination , the situation that the calibrating distance is too short
算法考慮到攝像機(jī)模型中的一階徑向畸變，巧妙地利用成像過(guò)程中的徑向約束（ rac ）分解攝像機(jī)參數(shù)，同時(shí)通過(guò)合理地組織參數(shù)的求解次序，使得經(jīng)由求解線性方程組就可以得到全部的攝像機(jī)參數(shù)，從而改變了以往攝像機(jī)rac標(biāo)定方法依賴于非線性優(yōu)化，以及對(duì)光照條件要求嚴(yán)格和標(biāo)定測(cè)定距離短的情況，使得rac方法較以往的算法更為精確、快速、簡(jiǎn)便，并且更加具有推廣價(jià)值。