fewer networks 中文意思是什麼
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In the paper, based on the existing literature research foundation an analog circuit catastrophic fault location approach by using feedforward networks with back ? propagation learning is realized. by this approach, the simulation require ments before test are reduced because fewer training samples are needed, and the fault location process is fast. this method is very efficient in location of single hard fault wit component tolerances. the measureme nt space feature and the general characterization concept of single and double soft fault in linear circuits are presented. according to this concept, a linear circuits soft fault location approach using subhidden layer bpnn is established with element tolerance, and it is shown that this approach is successful in fault location. a double fault feature extraction.,
本文在現有文獻理論研究的基礎上實現了採用bp演算法前向多層神經網路對直流測試下模擬電路硬故障的診斷方法。其特點是採用少量典型特徵樣本作為bp網路的訓練樣本，獲得訓練樣本的代價小，減少了測前工作量，同時診斷速度快，在考慮元件容差時仍有好的診斷效果。文中介紹了線性電路單一軟故障和雙軟故障所具有的電壓增量空間特性和統一特徵概念。 -
The result is fewer interruptions and better performance while conferencing on the public internet or on lan wan networks
結果當有關公眾的網際網路的或者有關lan與wan網路的會議時是少中斷和較好的性能。 -
T - s model is a novel fuzzy reasoning model which replaces the parameters of traditional reasoning system with linear partial equation. therefore, it can generate complicated nonlinear equation with fewer fuzzy rules. but the conclusional parameter is not a fuzzy rule but a linear equation, it can not be got from expert ' s experience and operational data directly. we must refine the parameter with some algorithm. by constructing t - s fuzzy neural networks we can solve the problem easily
T - s模型是一種新穎的模糊推理模型，它以線性局域方程取代了一般推理過程中的常數，因此可以用少量的模糊規則生成較復雜的非線性函數。但是由於結論參數是線性函數而非模糊數，所以規則不能直接從專家經驗和操作數據中直接得到，必須通過一定的演算法進行提煉。因此模型參數的辨識成為建立t - s型模糊系統的主要問題。
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