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采樣空間
典型空間
取樣空間
試樣空間
樣本空間
樣品空間

"sample" in Chinese : n. 1.樣品，貨樣。 2.標(biāo)本；榜樣，實(shí)例。 3.【統(tǒng) ...
"space" in Chinese : n. 1.空間；太空。 2.空隙，空地；場(chǎng)地；(火車輪船 ...
"denumerable sample space" in Chinese : 可數(shù)樣本空間
"discrete sample space" in Chinese : 離散型樣本空間; 離散樣本空間
"discretization sample space" in Chinese : 離散樣本空間
"point in the sample space" in Chinese : 樣本空間的點(diǎn)
"product sample space" in Chinese : 積樣本空間
"sample probability measure space" in Chinese : 樣本概率測(cè)度空間
"sample uniform, space sampling" in Chinese : 點(diǎn)群的取樣
"troubles inside the sample space" in Chinese : 區(qū)內(nèi)故障
"by sample" in Chinese : 憑樣品
"on sample" in Chinese : 憑樣本; 作樣品
"sample" in Chinese : n. 1.樣品，貨樣。 2.標(biāo)本；榜樣，實(shí)例。 3.【統(tǒng)計(jì)】典型取樣，抽檢查 ...
"to sample" in Chinese : 取樣品
"be on space" in Chinese : 投稿為生

Examples

Troubles inside the sample space
區(qū)內(nèi)故障
Initial sample spacing
初始采樣間距參數(shù)
Product sample space
積樣本空間
On constructing and optimization of sample spaces in calculation of classical probability
關(guān)于古典概率計(jì)算中樣本空間的構(gòu)造及優(yōu)化
A note on the method for constructing the confidence limits of parameters based on order relation in the sample space
基于樣本空間中序關(guān)系構(gòu)造參數(shù)置信限方法的一個(gè)注記
In the gain measurement , the sample spacing can be enlarged directly , yet the required maximum remains unchangeable
增益測(cè)量時(shí)可以將采樣間距直接增大，亦可有效地獲得所需的最大值。
As for the undivided linear sample space , the kernel function is needed to map onto another high dimension linear space
對(duì)于線性不可分的樣本空間，需要尋找核函數(shù)，將線性不可分的樣本集映射到另一個(gè)高維線性空間。
And find the reason that cause illusion is to choose the sample space wrongly , then explain the importance of choosing the sample space correctly
并分析了導(dǎo)致錯(cuò)覺的原因是錯(cuò)誤地選擇了樣本空間，進(jìn)而說明正確選擇樣本空間的重要性。
In this dissertation , we propose improved genetic algorithm and utilize it to search sample space for classification and evaluation with the best representative subset of training set
本文提出一種改進(jìn)的遺傳算法,利用改進(jìn)的遺傳算法搜索樣本空間,將得到的訓(xùn)練集的近似最優(yōu)代表性子集作為訓(xùn)練集去分類評(píng)估集。
Compared with conventional statistic classifier , the artificial neural network ( ann ) has been developed and applied to remote sensing data classification problem , which does n ' t need suppose parameterized distribution of sample space in advance
與傳統(tǒng)統(tǒng)計(jì)方法的分類器相比較，人工神經(jīng)網(wǎng)絡(luò)法不需要預(yù)先假設(shè)樣本空間的參數(shù)化統(tǒng)計(jì)分布，正在被越來越普遍的應(yīng)用于遙感圖像分類的研究。