表歸並排序 的英文怎麼說
中文拼音 [biǎoguībàngbèixù]
表歸並排序
英文
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In this dissertation, the research trends for the problem have been introduced ; the ‘ dim ’ and ‘ point ’ has been strictly defined in mathematics from machine vision and human vision ; the ideal clutter suppression system based on clutter predication and the realization and evaluation of evaluation index has been studied, in succession the clutter suppression technologies have been researched. firstly, the classic nonparametric algorithm has been analyzed in detail and systematically, for it ’ s weakness that it cannot remove the non - stationary clutter ideally, kalman filter algorithm for clutter suppression in 2d image signal has been built. secondly, fast adaptive kalman filter is presented based on fast wide - sense stationary areas partition algorithm : limited combination and division algorithm based on quarti - tree algorithm, new taxis filter route algorithm which can break through the limitation of the necessity of pixel neighborhood of 2d filter and laplace data model with two parameters which is perfectly suitable for the residual image of kalman clutter suppression
首先分析了經典的非參數法，對於四種具有代表性的核，從前述的三個性能評價方面做了分析和對比，指出了其速度快的優點和對非平穩圖像適應性差的弱點，針對非參數法的弱點，重點研究了對非平穩圖像適應良好的卡爾曼雜波抑制技術:建立了非平穩圖像的類自回歸模型，在此基礎上建立了二維卡爾曼濾波基礎的兩個方程:狀態方程和測量方程;建立了非平穩圖像準平穩區域快速劃分演算法:基於四叉樹法的有限分裂合併演算法;二維空間的基於k排序的濾波路線演算法，突破了空域濾波路線上區域相鄰的限制;在這些研究的基礎上實現了快速卡爾曼估計，實驗驗證了該方法相對逐點卡爾曼估計可以提高運算速度三倍左右;雜波抑制結果表明傳統的高斯性檢驗並不適合卡爾曼估計后的殘余圖像，由此建立了殘余圖像的雙參數拉普拉斯模型，實驗表明其可以完好的吻合殘余圖像的概率密度曲線。Thirdly, the short - term and long - term financial early - warning system is established based on the financial statements of marketing corporation in electric power, medicine and general merchandise. systematic method, efficiency coefficient method and linear regression method are applied in the short - term financial early - warning system from the aspect of cash flow, operating performance and function model ; growth periods method and management grade method are applied in the long - term financial earl y - warning system from the aspect of growing capability and financial stratagem. finally, lots of examples are given to validate these early - warning models, and some countermeasures are discussed for avoiding and eliminating the distress of enterprise
首先，介紹了企業財務預警的概念、功能和國內外的研究現狀；其次，闡明了企業財務預警的原理、程序和方法；再次，它以電力、醫藥和百貨行業的上市公司報表為資料，按照指標選取、標準判斷、警限設置和警度預報的步驟，從企業的現金流量、財務業績和函數模型三方面，分別運用系統化方法、功效系數法和線性回歸法構建了企業短期財務預警系統，從企業的成長能力和財務戰略兩方面，分別運用周期波動法和管理評分法構建了企業長期財務預警系統；最後，舉了大量實例對構建的各個預警模型進行考證，並從財務角度探討了企業的防警和排警對策。
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