probability samples 中文意思是什麼

probability samples 解釋
概率樣本
  • probability : n 1 或有；或然性。2 【哲學】蓋然性〈在 certainly 和 doubt 或 posibility 之間〉。3 【數學】幾率，...
  • samples : 采樣；樣本；樣條
  1. Random probability samples

    隨機概率抽樣
  2. The adaptation processing includes linear prediction coefficient adaptation and adaptation of quantization step size for residual signals. based on g. 726, we adopt a huffman coder to make use of probability statistic of bit cascade covering n ( n 1 ) samples generated from adpcm, in order to further reduce the bit rate. ng is lossless entropy coding, the speech quality of our improved algorithm should be same as that of g. 726 standard

    我們的研究和改進工作包括:研究最優非均勻自適應量化器，及其自適應演算法;研究波形預測函數，以及函數零點、極點的自適應演算法;基於每n （ n 1 ）個樣本所對應符號的概率統計，對預測殘差量化值再進行huffman編碼，進一步降低比特率。
  3. The thesis mainly recounts the detail questions about bayesian small sample theory and the important applications of the theory in engineering, and gives sufficient analyses and discussion of every step of accomplishing a precision evaluation when using small samples. in the thesis, the following issues are contained, such as how to get and denote the prior information, the consistence test of prior information and test samples of shooting range, the fusion of multi - source information, calculating of posterior probability, estimation with bayesian approach, how to constitute test evaluation project of different performance and calculate the risks of both sides are contained, and at last a kind of applied method to calculate the effectiveness is given

    論文主要敘述了有關bayes小樣本理論的一些具體問題，以及該技術在工程中的一些關鍵應用，對小樣本條件下精度鑒定的各個環節給予較充分的分析和討論，其中包括驗前信息的獲取、表示，驗前信息和靶場試驗樣本的一致性檢驗，多源信息的融合，驗后概率的計算， bayes方法在估計中的應用，試驗鑒定方案的制定，對不同戰標的評估方法和風險的計算等，最後對作戰效能的計算給出了一種工程中較實用的方法。
  4. Secondly, the paper shows the results from a great number of experiments of the weight algorithm that chooses samples by probability. the experiments point out that weight algorithm has a better generalization ability than the no weight algorithm. but a single weight algorithm is unstable and it needs tremendous time of calculation to combine many single algorithms into a stable one

    其次對按概率取樣本的有權值演算法進行了大量實驗，實驗結果顯示出按概率選擇樣本權值演算法比無權值演算法的總體性能更為優秀，但其個體演算法的不穩定性以及為了獲得穩定結果所需要的巨大計算時間使其不可能成為一種能廣泛應用的演算法。
  5. This paper presents a new face detection algorithm for color video images based on skin color and multimodal information fusion. first, this paper presents a new means for selecting skin samples ; and then comparing skin distribution in the eight color spaces and analyzing the adaptability for different skin patterns, poses a face initial orientation ' s method which uses the single gaussian model in the tsl color spaces, and calculates skin probability images ; afterwards comprehensive comparing three typical threshold value separating algorithms, put forwards a face separating method which bases on region growing and fuses multimodal informations ; final, raises a face confirming algorithm which fuses three shape features

    首先提出了?種新的膚色樣本選取方法；然後通過對八種色空間膚色分佈的比較以及不同膚色模型適應性的分析，提出了在tsl色空間上用單峰高斯模型模擬膚色分佈，求得膚色概率圖進行人臉初定位的方法；隨后在綜合比較三個典型閾值化分割演算法的基礎上，提出了融合多源信息進行區域生長分割人臉的演算法；最後提出了融合三個形狀特徵的人臉確認演算法。
  6. Comparing with non - bnyain methods, it ' s prominent featares lay in that it combines the prior and posterior information, which avoids the disadvantag of subjective bias caused by simply using the prior information only, of blind search caused by the incomplete sample information, of noise affection caused by simply using the sample information only if we choice a suitable priof, we can conduct the bayesian leaming effectively, so it fits the problems of data mining and machine leaming that possess charaters of probability and statistics, especially when the samples are rare

    與非貝葉揚方法相比，貝葉斯方法的特出特點是其學習機制可以綜合先驗信息和后驗信息，既可避免只使用先驗信息可能帶來的主觀偏見，和缺乏樣本信息時的大量盲目搜索與計算，也可避免只使用樣本信息帶來的噪音的影響只要合理地確定先驗，就可以進行有效的學習。因此，適用於具有概率統計特徵的數據採掘和機器學習（或發現）問題，尤其是樣本難得的問題
  7. Comparing of the ratio of 550nm emission intensity to 525nm in samples annealed at different temperature and times, the results obtained from a fit of the integrated intensity for these two emission indicated the change of radiative transition probability at different energy level are different

    通過比較不同退火溫度和時間樣品的兩者發光變化的不同，發現兩者的激發機理不同。通過比較不同樣品的525nm和550nm發射強度比值隨退火條件的變化以及這兩個發光的積分強度的變溫擬合結果說明退火對不同能級的輻射躍遷幾率的影響不同。
  8. This paper studies 3 kinds of algorithms : the viterbi algorithm, multiresolutional algorithm based on wavelet transformation and bayesian bootstrap algorithm. the viterbi algorithm is based on the hidden markov model theory and it is a kind of map estimation, this paper studies this algorithm and puts up an algorithm that suits for filtering in the presence of interference. multiresolutional algorithm takes full advantage of multiresolutional data, we can see it has a better filtering ability than the traditional filtering methods ; bootstrap algorithm is a recursive bayesian estimation, it describes the probability density function by the samples, so it can be used to nonlinear non - gaussion filtering, the simulation result of the two groundings is presented

    Viterbi演算法以隱馬爾可夫理論為基礎，是一種最大后驗概率估計方法，本文對該演算法進行了研究，給出了一種適合於非高斯干擾條件下的濾波方法；多分辨分析方法充分利用到了多解析度測量數據所包含的信息，從模擬結果中可以看出，該方法的濾波精度要高於傳統的濾波演算法；自主濾波方法是一種遞推貝葉斯估計演算法，它利用采樣點來描述目標狀態的概率密度函數，因而適用於非線性、非高斯條件下的濾波，本文分別對這兩種情況下的濾波進行了模擬。
  9. Then in this paper the author establishes the simulation model of the probability of smashing the submarine when the segregator of the submarine launched missile carrier sinking in the water and uses the monte carlo ( of or relating to a problem - solving technique that uses random samples and other statistical methods for finding solutions to mathematical or physical problems. ) to simulate the whole process. then the author carrier through much simulating computations and gives the smashing probability at different conditions

    在對分離體下沉的各種干擾因素進行了深入的分析后，建立了基於蒙特卡羅方法的潛射導彈運載器分離體砸艇概率的計算模型，並且進行了大量的計算機模擬試驗，分別對運載器採用平面彈道，偏航彈道在不同發射深度，不同發射艇速的情況下的分離體砸艇概率進行了模擬計算，給出了不同情況的砸艇概率。
  10. There are bogus surveys galore ? she takes commendable swipes at alfred kinsey and shere hite ? but very little based on proper, probability - weighted samples, and even fewer international comparisons

    虛假的調查太多了? ?她對阿爾弗雷德?金賽和雪莉?海德進行了抨擊，這值得贊揚? ?但很少有調查是基於恰當的、概率加權的樣本，基於國際比較的就更少了。
  11. Secondly, revise factor coefficient with probability distribution, which given by experienced experts. thirdly, use bayes statistic deducing method to bind together the income rate of prior distribution and sample in formation, which makes forecast stocks in shenzhen stock market as samples. work out the series of weakly income rate

    （ 2 ）對多元回歸的因子模型的各因子權重重做修正，將一些對金融市場有較透徹了解和豐富經驗的專家提供的信息引入，作出因子系數的概率分佈（並非隨意的主觀臆造） ，對模型的結果加以修正，以便提高模型的準確度。
  12. The instantaneous probability density function of the virtual stochastic process is evaluated, and then the probability density function of the basic random variable is obtained by employing the independent random samples

    利用獨立隨機抽樣的樣本值，即可獲取虛擬隨機過程的瞬時概率密度函數，進而獲得隨機變量的概率密度函數估計。
  13. How to estimate m ( x ) from the samples { ( xi, y, ) } has been one of the most importement things in probability and statistics

    如何由上述n個樣本對m （ x ）進行估計，一段時間成了概率、統計界研究的熱點之一。
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