For phase space reconstruction of ship - radiated noise , using auto correlation function and mutual information to select the delay - time , and using false nearest neighbors method to select the embedding dimension 從自相關(guān)函數(shù)及互信息嫡兩個方面討論了相空間重構(gòu)中延遲時間的選擇。
In order to reduce the disadvantageous influence of decision profiles ' scattering on fusion recognition , the decision profile is taken as target ' s feature vector and k - nearest neighbor method is applied to classify the target 為減少目標決策分布圖散布對融合識別效果的影響,提出采用k近鄰方法對目標的決策分布圖進行分類,以實現(xiàn)融合識別。
This paper uses kriging method to estimate rainfall in drainage basin , gives the results of kriging interpolation method , and compares it with inverse distance square method and nearest neighbor method 為此,嘗試采用克里格方法對流域雨量進行估值,并分別將年平均、月平均、時段雨量的插值結(jié)果與距離反比法以及最臨近法的插值結(jié)果進行了對比性檢驗。
The minimum embedding dimension can be determined by the false nearest neighbors method , and embedding dimension of determination component in noise condition can be determined precisely by this method which can avoid the phase space disturbance because of the higher embedding dimensions 采用偽最鄰近點法確定最小嵌入維數(shù),這種方法可以準確地確定含噪信號中確定性成分的最小嵌入維數(shù),避免嵌入維數(shù)過高導致相空間的混亂。
A variety of methods including the tabular comparison of data , the tabular comparison of similarity coefficient , the nearest neighbor method and the group - average method of hierarchical agglomerative classification were applied to investigate the forest communities in meizi lake area 森林植被樣地中以喬木層樹種的重要值為指標,采用紙條排隊法、群落相似系數(shù)分類法、最近鄰體法、組平均法對梅子湖森林植被樣地進行數(shù)量分類。
Then , because of the characteristic of complex engineering systems like fighters , such as modeling difficulty , multiplicity work situations , difficulty and expensiveness for test , a new kind of fast fault predictor is designed based on an improved k - nearest neighbor method , which neither need math model of system nor need data for train and knowledge 其次,針對殲擊機等復雜工程系統(tǒng)建模困難、工作情況多樣、試驗困難且代價高昂的特點,提出了一種改進k近鄰密度估計方法,設(shè)計了一種完全既不需要系統(tǒng)數(shù)學模型也不需要故障訓練數(shù)據(jù)和先驗知識的實時故障預報器。
This recognition method integrates traits of nearest neighbor method and k - neighbor method . its basic principle is to improve recognition reliability with tow additive thresholds . in addition , ternary threshold neighbor recognition method ’ s fast arithmetic based on c - average clustering and huffman tree is put forward 2 .本文在經(jīng)典統(tǒng)計模式識別方法的基礎(chǔ)上,結(jié)合了最近鄰識別法和k近鄰識別法的特點,給出一種三閾值近鄰識別方法,其基本原則是在尋找未知樣本的近鄰時,通過附加閾值的限制,進一步提高識別的可靠性。