GraphCut Minimization Library 转换成 VC++6.0 Class File
标签： Minimization GraphCut Library Class
上传时间： 2015-06-09
上传用户：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.
标签： Minimization Implement the two-level
上传时间： 2014-01-09
上传用户：无聊来刷下
Conjugate Gradient Minimization在梯度下降算法中有着重要应用。可以解决一些一般方法不容易解决的问题
标签： Minimization Conjugate Gradient 梯度
上传时间： 2014-01-12
上传用户：李彦东
Total variation image deconvolution_A majorization-Minimization approach
标签： majorization-Minimization deconvolution_A variation approach
上传时间： 2016-11-16
上传用户：xg262122
以L1-Minimization为核心的算法，近几年飞速进展，Compressive Sensing (Compressive Sampling) 已然成为数学领域和信号处理最前沿最热门的方向。最近一年多这种新形式的算法快速蔓延到模式识别界应用，论文质量高、算法效果好、而且算法一般都非常简单
标签： Minimization 核心 算法
上传时间： 2013-12-21
上传用户：我干你啊
Algorithms for Minimization Without Derivatives.pdf
标签： Minimization Derivatives Algorithms Without
上传时间： 2017-06-30
上传用户：璇珠官人
寻找函数的全局极小值，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.
上传时间： 2013-12-15
上传用户：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.
标签： independent kernel-ica implements algorithm
上传时间： 2014-01-17
上传用户：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
标签： identification considered features separati
上传时间： 2016-09-20
上传用户：FreeSky
