GraphCut Minimization Library 轉換成 VC++6.0 Class File
標簽： Minimization GraphCut Library Class
上傳時間： 2015-06-09
上傳用戶：wangchong
Implement the step 2 of two-level logic Minimization. Our goal is to find the minimum (exact minimum) sum-of-products expression for a given function.
標簽： Minimization Implement the two-level
上傳時間： 2014-01-09
上傳用戶：無聊來刷下
Conjugate Gradient Minimization在梯度下降算法中有著重要應用。可以解決一些一般方法不容易解決的問題
標簽： Minimization Conjugate Gradient 梯度
上傳時間： 2014-01-12
上傳用戶：李彥東
Total variation image deconvolution_A majorization-Minimization approach
標簽： majorization-Minimization deconvolution_A variation approach
上傳時間： 2016-11-16
上傳用戶：xg262122
以L1-Minimization為核心的算法，近幾年飛速進展，Compressive Sensing (Compressive Sampling) 已然成為數學領域和信號處理最前沿最熱門的方向。最近一年多這種新形式的算法快速蔓延到模式識別界應用，論文質量高、算法效果好、而且算法一般都非常簡單
標簽： Minimization 核心 算法
上傳時間： 2013-12-21
上傳用戶：我干你啊
Algorithms for Minimization Without Derivatives.pdf
標簽： Minimization Derivatives Algorithms Without
上傳時間： 2017-06-30
上傳用戶：璇珠官人
尋找函數的全局極小值，global Minimization of contrast function with random restarts the data are assumed whitened (i.e. with identity covariance matrix). The output is such that Wopt*x are the independent sources.
上傳時間： 2013-12-15
上傳用戶：康郎
The kernel-ica package is a Matlab program that implements the Kernel ICA algorithm for independent component analysis (ICA). The Kernel ICA algorithm is based on the Minimization of a contrast function based on kernel ideas. A contrast function measures the statistical dependence between components, thus when applied to estimated components and minimized over possible demixing matrices, components that are as independent as possible are found.
標簽： independent kernel-ica implements algorithm
上傳時間： 2014-01-17
上傳用戶：yiwen213
The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit Minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order
標簽： identification considered features separati
上傳時間： 2016-09-20
上傳用戶：FreeSky
