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<nav id="60yqo"></nav> This code is to Estimate the parameter of model of Mixture Gauss which is popular model used in pattern classification . JAVA 寫的估計復合高斯模型中的參數
標簽： model parameter Estimate Mixture
上傳時間： 2015-04-10
上傳用戶：kikye
理解并掌握分析回溯算法效率的方法。 使用Estimate算法就8皇后問題給出效率估算
上傳時間： 2014-01-21
上傳用戶：xuanjie
Estimate the orientation of fingerprint
標簽： orientation fingerprint Estimate the
上傳時間： 2013-12-23
上傳用戶：cursor
Use DCT-LMS algorithm with recursions on C to Estimate optimum weight vectors for linear estimation.
標簽： recursions estimation algorithm Estimate
上傳時間： 2014-01-10
上傳用戶：13160677563
To Estimate the input-output mapping with inputs x ％ and outputs y generated by the following nonlinear, ％ nonstationary state space model: ％ x(t+1) = 0.5x(t) + [25x(t)]/[(1+x(t))^(2)] ％ + 8cos(1.2t) + process noise ％ y(t) = x(t)^(2) / 20 + 6 squareWave(0.05(t-1)) + 3 ％ + time varying measurement noise ％ using a multi-layer perceptron (MLP) and both the EKF and ％ the hybrid importance-samping resampling (SIR) algorithm.
標簽： input-output the generated following
上傳時間： 2014-01-05
上傳用戶：royzhangsz
This program is a new way to Estimate the coherence function. It s based on the MVDR and is much more reliable than the classical Welch s method implemented in MATLAB. There are 2 programs: the main program called coherence_MVDR.m and and an example, called illustrate.m, that calls the main function to show how it works. There also included 2 papers that we published on this algorithm.
標簽： coherence the Estimate function
上傳時間： 2016-07-03
上傳用戶：athjac
功率譜估計的相關資料Power spectrum Estimate of relevant information
標簽： information spectrum Estimate relevant
上傳時間： 2013-12-27
上傳用戶：dbs012280
This function provides an ARMA spectral Estimate which is maximum entropy satisfying correlation constraint (number of poles)and cepstrum constrains (number of ceros)
標簽： correlation satisfying function Estimate
上傳時間： 2013-12-21
上傳用戶：朗朗乾坤
This function calculates Akaike s final prediction error ％ Estimate of the average generalization error. ％ ％ [FPE,deff,varest,H] = fpe(NetDef,W1,W2,PHI,Y,trparms) produces the ％ final prediction error Estimate (fpe), the effective number of ％ weights in the network if the network has been trained with ％ weight decay, an Estimate of the noise variance, and the Gauss-Newton ％ Hessian. ％
標簽： generalization calculates prediction function
上傳時間： 2014-12-03
上傳用戶：maizezhen
This function calculates Akaike s final prediction error ％ Estimate of the average generalization error for network ％ models generated by NNARX, NNOE, NNARMAX1+2, or their recursive ％ counterparts. ％ ％ [FPE,deff,varest,H] = nnfpe(method,NetDef,W1,W2,U,Y,NN,trparms,skip,Chat) ％ produces the final prediction error Estimate (fpe), the effective number ％ of weights in the network if it has been trained with weight decay, ％ an Estimate of the noise variance, and the Gauss-Newton Hessian. ％
標簽： generalization calculates prediction function
上傳時間： 2016-12-27
上傳用戶：腳趾頭
