With having tutor study style , this system adopts a sort of new error function to adjust its parameter systemically according to the status of sample in the course of training 采用有導(dǎo)師學(xué)習(xí)方式,根據(jù)樣本對(duì)在訓(xùn)練過(guò)程中的情況,系統(tǒng)地調(diào)整其參數(shù)。
Switch states of mc are obtained when the output voltage error function is minimized , thus the optimum combination of switch states is derived for the closed - loop control of mc 根據(jù)最小誤差函數(shù)確定矩陣變換器開關(guān)模式,實(shí)現(xiàn)了系統(tǒng)閉環(huán)控制時(shí)開關(guān)狀態(tài)的優(yōu)化組合。
1 romdhani s , blanz v , vetter t . face identification by fitting a 3d morphable model using linear shape and texture error functions . in proc . 7th european conf 并且,通過(guò)分塊仿射變換得到的紋理已經(jīng)損失了形狀的信息,紋理和形狀的相關(guān)性已經(jīng)減弱,過(guò)強(qiáng)的假設(shè)使得結(jié)果的推廣性能減弱。
The probability of normal r . v . with absolute value less then and equal to one , two , and three unit standard deviations are calculated from error function , the cumulate probability distribution of normal density 常態(tài)分布隨機(jī)變數(shù)絕對(duì)值小于等于一個(gè)、兩個(gè)、三個(gè)標(biāo)準(zhǔn)差之機(jī)率分別代入累積機(jī)率分布函數(shù)(誤差函數(shù))算出其對(duì)應(yīng)之機(jī)率。
Based on the output - voltage error function , a novel time discrete modulation technique is proposed for matrix converters ( mcs ) and time - discrete difference equations of a mc circuit are derived 摘要針對(duì)矩陣變換器調(diào)制方式的特點(diǎn),提出了基于輸出電壓誤差函數(shù)分析的矩陣變換器離散調(diào)制技術(shù),推導(dǎo)了基于時(shí)間離散和差分原理的電路方程。
Firstly , studied feed - forward neural network and put forward a new algorithm on bp network , called bp algorithm based on robust error function ( bparef ) , and the algorithm is proved to be effective for approaching nonlinear system 首先研究了前饋神經(jīng)網(wǎng)絡(luò),提出了基于魯棒誤差函數(shù)的bp神經(jīng)網(wǎng)絡(luò)的算法,并且驗(yàn)證了其對(duì)非線性系統(tǒng)逼近的有效性。
Back analysis of thermal and mechanics parameters are carried out by using dfp method and improving minimum two - multiplied error function based on the practical datas of temperature and strain of the hole 結(jié)合引水洞的溫度和應(yīng)變實(shí)測(cè)資料,利用考慮時(shí)間效應(yīng)、無(wú)量綱化的最小二乘誤差函數(shù),采用梯度優(yōu)化方法中變尺度方法對(duì)其熱、力學(xué)參數(shù)進(jìn)行了確定性反演。
At present , during the course of bp neural network ' s learning and training , we often adopt the algorithm of back - error propagation , which is based on global error function ' s gradient descent 特別是bp網(wǎng)絡(luò)近年來(lái)廣泛應(yīng)用于模式識(shí)別、預(yù)測(cè)評(píng)估等領(lǐng)域,并取得良好的效果。目前bp網(wǎng)絡(luò)采用誤差逆?zhèn)鞑ニ惴▽W(xué)習(xí)訓(xùn)練神經(jīng)網(wǎng)絡(luò),該算法是基于網(wǎng)絡(luò)誤差函數(shù)梯度下降的。
At present , during the course of bp neural network ' s learning and training , we often adopt the algorithm of back - error propagation , which is based on global error function ' s gradient descent , whose essence is a point - to - point search algorithm 目前bp神經(jīng)網(wǎng)絡(luò)采用誤差逆?zhèn)鞑ニ惴▽W(xué)習(xí)訓(xùn)練神經(jīng)網(wǎng)絡(luò),該算法是基于網(wǎng)絡(luò)誤差函數(shù)梯度下降的,其本質(zhì)是點(diǎn)到點(diǎn)的搜索方法。