ensemble of function 中文意思是什麼
ensemble of function
解釋
函數的總數-
The communication system ' s performance is briefly analyzed by channel capacity, which is a function of bit error rate ( ber ). the decision rule is based on the most likelihood method. for reproducing the original binary signals more correctly, time scale transformation method and the approach of ensemble average probability of error bits are introduced
通過理論分析和模擬實驗，本文研究了這個非線性數字通信系統性能，給出了誤碼率和通道容量公式，提出了系統參數調節方法，採用最大似然法設計了適合這個系統輸出的判決規則。 -
Abstract : on the basis of equal probability principle, boltzmann statistics and ensemble statistics, this paper has derived the statistical distribution function on multimember system in the quasi - independent particles and obtained the equivalence between boltzmann statistics and ensemble statistics for multimember system
文摘:利用平衡態統計物理的等概率原理，玻耳茲曼統計法和系綜統計法，導出在平衡狀態下多種近獨立粒子系統的粒子數分佈.結果表明，對于宏觀系統而言，玻耳茲曼統計和系綜統計是等價的 -
Then the unified approach can be applied to it to acquire the ensemble random evolutionary response. since the normal probability density function ( pdf ) may lead to instability of some sample systems when the random parameters taking sufficiently small negative values, an arch - like pdf and a more adaptable - pdf, together with the matching chebyshev polynomial approximation and gegenbauer polynomial approximation, are suggested. numerical examples show that the suggested methods are effective
相比較而言，隨機模擬法的結果無疑是最可靠的，但是它的計算量嫌大；隨機攝動法的計算量遠小於隨機模擬法，但是它要求隨機攝動量必須是一個小量；正交展開法的計算精度好於隨機攝動法，其得到結果與隨機模擬法得到的結果幾乎吻合，其計算量略多於隨機攝動法，但與隨機模擬法相比要少的多，不過計算前的準備工作較費時。 -
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的支持向量機容易因"單點失效"而危害系統安全.提出一種基於支持向量機集成的方法來進行入侵檢測.它採用負相關學習技術，在誤差項中使用相關性懲罰因子使得生成的分類器有更好的多樣性和精度;演算法採用進化策略來自動地確定個體支持向量機的超參數，避免了需要了解問題的先驗知識;最後，採用集成技術來組合個體支持向量機的檢測結果.模擬實驗表明這一方法有更好的檢測性能，並且這種分散式并行檢測方法有利於增加入侵檢測系統的魯棒性
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