最大期望演算法 的英文怎麼說

中文拼音 [zuìdàqīwàngyǎnsuànfǎ]
最大期望演算法 英文
expectation-maximization algorithm
  • 最 : 副詞（表示某種屬性超過所有同類的人或事物） most; best; worst; first; very; least; above all; -est
  • 期 : 期名詞[書面語]1. （一周年） a full year; anniversary 2. （一整月） a full month
  • 望 : Ⅰ動詞1 （向遠處看） look over; gaze into the distance; look far into the distance 2 （探望） visi...
  • 演 : 動詞1 （演變; 演化） develop; evolve 2 （發揮） deduce; elaborate 3 （依照程式練習或計算） drill;...
  • 算 : Ⅰ動詞1 （計算數目） calculate; reckon; compute; figure 2 （計算進去） include; count 3 （謀劃;計...
  • 法 : Ⅰ名詞1 （由國家制定或認可的行為規則的總稱） law 2 （方法; 方式） way; method; mode; means 3 （標...
  • 期望 : 1. （抱有希望的想法） hope; expectation 2. （希望; 期待） hope; expect; wish
  1. One of which is based on the maximum signal - to - noise ratio ( msnr ) criterion, it can improve the performance of the array system only when the processing gain of the given cdma system is high enough such that the desired signal can become dominant after dispreading. the other is based on the maximum signal - to - interference - plus - noise ratio ( msinr ) criterion, and it has well performance when strong interferers occur

    一種是基於最大信噪比準則的演算法，該演算法適用於cdma系統的處理增益比較大，即解擴以後期望用戶信號遠大於干擾信號的情況；另一種是基於最大信干噪比準則的演算法，該演算法在強干擾存在的情況依然有較好的性能。
  2. Efficient expetation maxmization algorithms are developed for fitting the hmms to observational signal data

    有效的最大期望演算法可以將hmms同觀察信號數據結合起來。
  3. Band selection methods are more proper for hardware realization and the last method is chosen for dimensionality reduction of hyperspectral image processed by the hardware platform. secondly, rx, gmrf and sem, three representational algorithms of anomaly detection are studied

    其次，研究了具有代表性的三種奇異檢測演算法: rx演算法、基於高斯馬爾可夫隨機場模型（ gmrf ）的檢測演算法和基於隨機最大期望（ sem ）分類的檢測演算法。
  4. An efficient implementation of this framework is presented, for segmenting two motions ( foreground and background ) using two frames. the expectation - maximization algorithm is used to determine the two motions and calculate the label probability for each edge. the best motion labeling for these regions is determined using simulated annealing

    針對前景和背景兩種運動分割的情況，本文給出了一種基於貝葉斯分割框架的有效實現，它使用最大期望（ em ）演算法來估算邊緣的標定概率，並通過模擬退火演算法來完成這些分割區域的最佳運動標定。
  5. In this paper, at first we introduce the purpose, significance, domestic and foreign research present situation of network tomography. we give a detailed presentation on tomography and measure methods by different classified method. after introduced the elementary knowledge about tomography, we elaborate in detail the derivative process of multicast - based direct estimator algorithm, expectation maximum algorithm and unicast - based loss inference method

    本文首先介紹了網路透視的目的、意義和研究現狀，按照不同的分類方法介紹了幾種主要的網路測量和網路透視方法;在介紹了網路透視技術的基礎知識后，詳細闡述了多播透視演算法中直接估計演算法（ directestimator ）和最大期望演算法（ expectationmaximum ）的推理過程，以及單播透視的丟包率推理演算法。
  6. Dbf algorithms for 2d planar array based on the algorithms for 1d array are discussed in this paper. the author ' s main contributions include research of the adaptive digital beamforming algorithm, which control both amplitude and phase of each array element : diagonal loading qrd - smi algorithm. research of two phase - only dbf algorithms : small phase perturbation restriction algorithm and maximum gain of the expected direction restriction algorithm

    面陣的數字波束形成演算法是面陣dbf技術的關鍵，本文在現有的一維數字波束形成演算法基礎上，研究了二維面陣的數字波束形成演算法，主要工作有：面陣的幅度相位全控制自適應數字波束形成演算法? ?對角加載qrd - smi演算法的研究；兩種面陣唯相位（ phase - only ）數字波束形成演算法? ?小相位擾動約束演算法和期望方向增益最大約束演算法的研究；面陣的數字多波束形成演算法? ?二維fft多波束的研究，以及fft在可編程邏輯器件中的實現。
  7. Such integra ting feature vector is used for building k dim e nsion gaussian m odel, whose param e ters are estim ated by an expectation - m a xi m i zation ( em ) algorithm, and then the resulting block - cluster m e mberships provide a segm entation of th e im age. after segm ented, a m e thod of param e ter - trimm e d average for describing re gion is proposed, of which the param e ter is decided by area and position of region dire ctly. the sim ilarity m easure between two im ages is defined by integrating properties of all regions in the im age

    文中先將圖像分成4 4小塊，各塊的顏色、紋理、位置特徵構成8維的特徵空間；在該空間中對得到的8維特徵矢量建立一個k維高斯模型，應用期望最大em演算法估計模型參數，產生的塊特徵-聚類隸屬度函數實現對圖像的分割；為減小分割演算法不確定性對檢索效果的不良影響，對得到的區域採用參數均衡平均特徵表示，其中參數的確定直接與區域的面積、位置有關。
分享友人
分享到 Line

分享到臉書