neural classifier中文是什么意思

發(fā)音:

中文翻譯
造句

《英漢醫(yī)學詞典》neural classifier
神經(jīng)分類器

neural adj. 【解剖學】神經(jīng)(系統(tǒng))的；神經(jīng)中樞的；【解剖學】背的，背側的。 adv. -ly
classifier n. 1.分類者。 2.【礦物】分級機。 3.【化學】分粒器。 4.(漢語等中的)量詞。
neural analyzer 神經(jīng)分析器
neural arch 【動物；動物學】髓弓。
neural assembly 神經(jīng)集合
neural atrophy 神經(jīng)病性肌萎縮; 神經(jīng)性萎縮
neural axis 軸索神經(jīng)軸
neural canal 【解剖學】神經(jīng)溝。
neural cell 神經(jīng)細胞
neural circuit 神經(jīng)回路
neural coding 神經(jīng)編碼
neural computatio 神經(jīng)計算神經(jīng)系統(tǒng)處理信息的一種基本算法
neural computation 神經(jīng)計算神經(jīng)系統(tǒng)處理信息的一種基本算法, 即并行分布處理。
neural computing 神經(jīng)計算學
neural control 神經(jīng)控制
neural correlate 神經(jīng)相關物
neural crest 神脊; 神經(jīng)冠; 神經(jīng)脊; 神經(jīng)嵴
neural cyst 神經(jīng)系囊腫
neural discharge 神經(jīng)沖動發(fā)放
neural ectoderm 神經(jīng)外胚層
neural encoding 神經(jīng)編碼過程
neural engineering 神經(jīng)工程學
neural epithelium 感覺上皮; 神經(jīng)上皮
neural facilitation 神經(jīng)易化
neural flap 神經(jīng)皮瓣

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例句與用法

Our results suggest that ga based neural classifiers are robust and effective in finding optimal subsets of features from large data sets
結果顯示，基因演算法結合類神經(jīng)分類器篩選特征值法是有效且穩(wěn)健的。
With this method, it is direct and convenient to construct a neural classifier . experimental results show that the covering method is promising for solving prpls
這樣，神經(jīng)分類器的構造變得直觀、容易，實驗結果表明覆蓋方法對于解決大規(guī)模問題是很有潛力的方法。
This method combines a genetic algorithm with an artificial neural network classifier, such as back-propagation ( bp ) neural classifier, radial basis function ( rbf ) classifier or learning vector quantization ( lvq ) classifier
此方法結合基因演算法與類神經(jīng)分類器，如倒傳遞分類器、放射基底函數(shù)分類器以及學習矢量量化分類器。
Recently a covering method for feed-forward neural network design has been proposed by professor zhang ling . based on the sphere neighborhood model, this method transforms the design of neural classifiers to a geometrical covering problem
近來張鈴教授提出了一種前饋神經(jīng)網(wǎng)絡設計的覆蓋方法，它以球面領域模型為基礎，使得神經(jīng)網(wǎng)絡的設計轉化為幾何覆蓋問題。
(5 ) a series of design methods of classifiers are proposed, including the classifier based on the generalized inverse and the probabilistic reasoning method ( prm ), a new self-adaptive kohonen clustering network which overcomes the shortcomings of the conventional clustering algorithms, and the fuzzy neural classifier . the experimental study efface recognition is presented based on the combination of multi-feature multi-classifier . ( 6 ) this paper proposes a hybrid feature extraction method for face recognition, which is a combination of the eigen matrix, fisher discriminant analysis, and the generalized optimal set of discriminant vectors
(5)對圖象分類器設計方法進行研究，主要包括：提出了一種基于廣義逆和概率推理的分類器設計方法；提出了一種新的自適應模糊聚類算法；提出了基于模糊神經(jīng)網(wǎng)絡的分類器設計方法；并對多特征多分類器組合方法在人臉識別中進行實驗研究；(6)提出了一種只要一個訓練樣本就能解決人臉識別問題的新方法，該方法結合了特征矩陣、fisher最優(yōu)鑒別分析和廣義最優(yōu)鑒別分析方法的優(yōu)點。

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