error function中文是什么意思

發(fā)音:

中文翻譯
造句

貧差函數(shù)
誤差函數(shù)

error n. 1.錯(cuò)誤；失錯(cuò)。 2.謬見，誤想；誤信；誤解。 3 ...
function n. 1.功能，官能，機(jī)能，作用。 2.〔常 pl.〕職 ...
cef complementary error function 誤差修補(bǔ)功能
co-error function 余誤差函數(shù)
complementary error function 補(bǔ)余誤差函數(shù); 余誤差函數(shù)
complemented error function 補(bǔ)余產(chǎn)差函數(shù); 補(bǔ)余誤差函數(shù)
error function complement 補(bǔ)余誤差函數(shù); 余誤差函數(shù)
error function diffusion 誤差函數(shù)擴(kuò)散
error function distribution 誤差函數(shù)分布
error function erf 貧差函數(shù)
error function integral 誤差函數(shù)積分
error function table 誤差函數(shù)表
error function test 誤差函數(shù)試驗(yàn)
error measuring function 誤差測量函數(shù)
error reporting function 錯(cuò)誤報(bào)告函數(shù)
error tra fer function 誤差傳遞函數(shù)
error transfer function 誤差傳遞函數(shù)
gauss error function 高斯誤差函數(shù)
high-frequency error function 高頻誤差函數(shù)
hyperbolic error function 雙曲線函數(shù)
range error function 距離誤差函數(shù)
sine-cosine function error 正余弦函數(shù)誤差
error 1 invalid function number 無效函數(shù)號(hào)
error 34 invalid function result type 無效的函數(shù)結(jié)果類型
be in error 弄錯(cuò)了

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例句與用法

Using the first order and the second order derivative information of the network error function to the learning rate factor / / and the momentum factor ? , dynamic optimization of the learning rate factor / / and the momentum factor ? is obtained during the network training process , which efficiently speeds up the network learning rate
并利用網(wǎng)絡(luò)誤差函數(shù)對訓(xùn)練速率系數(shù)和沖量系數(shù)的一階和二階導(dǎo)數(shù)信息，在網(wǎng)絡(luò)訓(xùn)練過程中動(dòng)態(tài)優(yōu)化調(diào)整訓(xùn)練速率系數(shù)和沖量系數(shù)，有效地加快了網(wǎng)絡(luò)的訓(xùn)練速度。
Aimed at the parameter estimation and model reduction problems of non - linear systems in noisy environment , a class of particle swami optimization ( pso ) approach with hypothesis test is proposed , named psoht , which estimates parameters by using pso operator in conjunction with evaluation and comparison in statistical sense to minimize mean square error function
摘要針對噪聲環(huán)境下的非線性系統(tǒng)參數(shù)估計(jì)和模型降階問題，提出了一種帶假設(shè)檢驗(yàn)的微粒群優(yōu)化算法( psoht ) ，以最小化平均平方誤差為目標(biāo)，結(jié)合統(tǒng)計(jì)意義下的評(píng)價(jià)和比較，通過微粒群操作進(jìn)行參數(shù)估計(jì)。
The individual svm is prone to fail in the intrusion detection for the fragility of being attacked . this paper addresses a method using a support vector machines ensemble approach based on negative correlation learning for intrusion detection . using a correlation penalty term in the error function , the aggregate members can be accurate and diverse . and the evolutionary strategy is considered as the best way to automatically determine the individ . ual svms hyperparameters . at last we combine the results of all individual svms using ensemble technique . this distributed parallel detection can strengthen the robustness of the system . simulation results show the effectiveness of the method presented in this paper
在入侵檢測中使用單個(gè)的支持向量機(jī)容易因"單點(diǎn)失效"而危害系統(tǒng)安全.提出一種基于支持向量機(jī)集成的方法來進(jìn)行入侵檢測.它采用負(fù)相關(guān)學(xué)習(xí)技術(shù),在誤差項(xiàng)中使用相關(guān)性懲罰因子使得生成的分類器有更好的多樣性和精度;算法采用進(jìn)化策略來自動(dòng)地確定個(gè)體支持向量機(jī)的超參數(shù),避免了需要了解問題的先驗(yàn)知識(shí);最后,采用集成技術(shù)來組合個(gè)體支持向量機(jī)的檢測結(jié)果.仿真實(shí)驗(yàn)表明這一方法有更好的檢測性能,并且這種分布式并行檢測方法有利于增加入侵檢測系統(tǒng)的魯棒性
Two distinct bp training algorithms on multilayer perceptron type neural - network are developed to improve the trained network ' s quickness , robustness and generality . they are brought out from the combination of existing investigations - dynamic learning rate , momentum terms and quadratic function of weights , and amendment of desired error function respectively . the simulative results of rotating machinery fault pattern classification illustrated the effectiveness of the new algorithms
針對多層感知器神經(jīng)網(wǎng)絡(luò)的標(biāo)準(zhǔn)bp訓(xùn)練算法存在推廣能力差和訓(xùn)練速度慢等缺陷，首先結(jié)合已有的研究成果，給出了一種動(dòng)態(tài)學(xué)習(xí)率和動(dòng)量項(xiàng)相結(jié)合，并在誤差函數(shù)中引入網(wǎng)絡(luò)權(quán)值的二次型函數(shù)項(xiàng)的改進(jìn)訓(xùn)練算法，提高了網(wǎng)絡(luò)的快速性和推廣能力。
The load of the dc motor has a great influence on the tracking effect of speed control system , so a kind of load disturbance observer is constructed to compensate the load disturbance , and a new variable structure controller is designed by employing lyapunov speed error function
針對實(shí)際直流電機(jī)負(fù)載對速度控制系統(tǒng)跟蹤效果有較大影響的情況，提出了一種重構(gòu)軋制負(fù)載擾動(dòng)的觀測器，進(jìn)而對負(fù)載擾動(dòng)進(jìn)行前饋補(bǔ)償控制，設(shè)計(jì)了一種新的利用lyapunov速度誤差函數(shù)構(gòu)造的變結(jié)構(gòu)魯棒控制器。
In the design of corpus , we carefully analyze the syllable distribution of corpus th - coss , then classify the prosodic characters of this corpus and present out the distribution of every prosodic character . based on prosodic character vector , we construct an error function which is used to select original corpus for simulation system , and show the distribution of prosodic characters for the original corpus . greedy algorithm and corpus self - adaptive process are expatiated to set theoretical foundation for text material search
在語料庫分析與設(shè)計(jì)方面,首先統(tǒng)計(jì)th - coss語料庫中音節(jié)分布情況,給出th - coss語料庫韻律特征分類,并對每一種韻律特征進(jìn)行統(tǒng)計(jì),然后構(gòu)造了一個(gè)基于韻律特征向量的誤差函數(shù),并采用該誤差函數(shù)提取語料組成模擬系統(tǒng)的初始語料庫,分析該庫的韻律特征分布,最后闡述了greedy算法與語料自適應(yīng)過程,為文本語料的搜索打下理論基礎(chǔ)。
In order to improve the generalization ability and to make the system more accordant to the practical requirement , the paper introduces the k - l information distance to the error function of the traditional bp algorithm . the simulation proves that the generalization ability of the system trained with the modified algorithm is much better than that of other algorithms
為了進(jìn)一步改進(jìn)系統(tǒng)的泛化能力，使其滿足報(bào)價(jià)的實(shí)際需要，本文利用神經(jīng)網(wǎng)絡(luò)的概率描述，通過研究k - l信息距離和神經(jīng)網(wǎng)絡(luò)泛化能力的關(guān)系，構(gòu)造了一個(gè)新的神經(jīng)網(wǎng)絡(luò)學(xué)習(xí)誤差函數(shù)，并將此法與其它各種算法的泛化結(jié)果進(jìn)行比較。

更多例句： 1 2 3 4

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