一個聚類算法用K-mean處理后迭代，論文發表在PAK
上傳時間： 2013-12-09
上傳用戶：66666
Generate 100 samples of a zero-mean white noise sequence with variance , by using a uniform random number generator. a Compute the autocorrelation of for . b Compute the periodogram estimate and plot it. c Generate 10 different realizations of , and compute the corresponding sample autocorrelation sequences , and . Compute the average autocorrelation sequence as and the corresponding periodogram for . d Compute and plot the average periodogram using the Bartlett method. e Comment on the results in parts (a) through (d).
標簽： zero-mean Generate sequence variance
上傳時間： 2016-03-04
上傳用戶：朗朗乾坤
Analysis of PHY waveform Peak to Mean Ratio and Impact on RF Amplification
標簽： Amplification Analysis waveform Impact
上傳時間： 2014-01-15
上傳用戶：hgy9473
mean shift
上傳時間： 2016-03-14
上傳用戶：huql11633
Please read them carefully before you write the package to their specific functions (at least 20 characters). As far as possible not to let the station for the time you have spent on that amendment. Have to extract the password to the password
標簽： carefully functions specific package
上傳時間： 2016-03-30
上傳用戶：小儒尼尼奧
多項式曲線擬合 任意介數 Purpose - Least-squares curve fit of arbitrary order working in C++ Builder 2007 as a template class, using vector<FloatType> parameters. Added a method to handle some EMathError exceptions. If do NOT want to use this just call PolyFit2 directly. usage: Call PolyFit by something like this. CPolyFit<double> PolyFitObj double correlation_coefficiant = PolyFitObj.PolyFit(X, Y, A) where X and Y are vectors of doubles which must have the same size and A is a vector of doubles which must be the same size as the number of coefficients required. returns: The correlation coefficient or -1 on failure. produces: A vector (A) which holds the coefficients.
標簽： Least-squares arbitrary Purpose Builder
上傳時間： 2013-12-18
上傳用戶：宋桃子
k-mean算法演示，利用手工輸入點通過k類自動聚合
上傳時間： 2016-04-09
上傳用戶：shanml
c-mean聚類算法源代碼，通過對輸入數據進行訓練和分類類別設定，能夠得到數據的聚類圖。
上傳時間： 2013-12-26
上傳用戶：colinal
k－mean算法的源碼，對聚類非常有用！！可以直接使用！
上傳時間： 2016-04-21
上傳用戶：ZJX5201314
Generate the digital AWGN signal n[k] (sampled n(t)) by generating zero mean Gaussian random variables independently (separately) for each k MATLAB function random.
標簽： generating Generate Gaussian digital
上傳時間： 2014-01-15
上傳用戶：sammi
