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Description: 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. -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.
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Size: 37888 |
Author: 林力宏 |
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Description: The Rudin-Osher-Fatemi total variation (TV) denoising technique poses the problem of denoising as a minimization problem
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Size: 1024 |
Author: fangfei_666 |
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Description: Author: Xavier Bresson (％ Last version: Aug 3, 2008
％ For more information: X. Bresson and T.F. Chan, "Fast Minimization of the Vectorial Total Variation Norm and Applications to Color Image
Processing", CAM Report 07-25-Author: Xavier Bresson ( Last version: Aug 3, 2008 For more information: X. Bresson and TF Chan, Fast Minimization of the Vectorial Total Variation Norm and Applications to Color ImageProcessing , CAM Report 07-25
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Size: 54272 |
Author: 代松 |
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Description: 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-Conjugate Gradient Minimization in the gradient descent algorithm has important applications. General approach can solve some difficult problems
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Size: 3072 |
Author: ZhangGeng |
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Description: Software for energy minimization with graph cuts。-Software for energy minimization with graph cuts.
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Size: 43008 |
Author: 余丽红 |
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Description: DFA状态最少化的算法，即DFA的最小化-DFA state minimization algorithm, namely, DFA Minimization
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Size: 3072 |
Author: 侯坤 |
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Description: Total variation image deconvolution_A majorization-minimization approach
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Size: 77824 |
Author: Binjie Qin |
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Description: 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-To L1-minimization as the core of the algorithm, the rapid progress in recent years, Compressive Sensing (Compressive Sampling) has become the field of mathematics and signal processing the forefront of the most popular direction. Recently, more than a year this new form of pattern recognition algorithm for the rapid spread to industry applications, high-quality paper, the algorithm better, but are generally very simple algorithm
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Size: 16139264 |
Author: yuhua |
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Description: Dense Matching using energy minimization
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Size: 7168 |
Author: ircman |
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Description: Dfa minimization from nfa
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Size: 4096 |
Author: Jeff |
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Description: This package contains code for solving seven optimization problems.
-The main directory contains MATLAB m-files which contain simple examples for each of the recovery problems. They illustrate how the code should be used (it is fairly straightforward). The prefixes on the example files are as follows:
"l1eq" = L1 minimization with equality constraints,
"l1qc" = L1 minimization with quadratic (L2 norm) constraints,
"l1decode" = L1 norm approximation (for channel decoding),
"11dantzig" = L1 minimization with minimal residual correlation (the Dantzig selector).
"tveq" = TV minimization with equality constraints,
"tvqc" = TV minimization with quadratic constrains,
"tvdantzig" = TV minimization with minimal residual correlation.
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Size: 365568 |
Author: liuhua |
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Description: 基于可变区域能量最小化拟合的图像分割方法的图像分割-Variable region-based energy minimization method of fitting the image segmentation of the image segmentation
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Size: 2011136 |
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Description: L1 minimization and compressive sensing
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Size: 244736 |
Author: Joey |
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Description: 基于图割的能量最小化演示文稿。本人整理的，进一步理解图割理论的知识-Based on graph cut energy minimization of the presentation. I am finishing, and further understanding of the theory of knowledge in cutting plan
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Size: 271360 |
Author: 王锐 |
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Description: This a demonstration of how to find a minimum of a non-smooth
objective function using the Genetic Algorithm (GA) function in the
Genetic Algorithm and Direct Search Toolbox. Traditional derivative-based
optimization methods, like those found in the Optimization Toolbox, are
fast and accurate for many types of optimization problems. These methods
are designed to solve smooth , i.e., continuous and differentiable,
minimization problems, as they use derivatives to determine the direction
of descent. While using derivatives makes these methods fast and
accurate, they often are not effective when problems lack smoothness,
e.g., problems with discontinuous, non-differentiable, or stochastic
objective functions. When faced with solving such non-smooth problems,
methods like the genetic algorithm or the more recently developed pattern
search methods, both found in the Genetic Algorithm and Direct Search
Toolbox, are effective alternatives. -This is a demonstration of how to find a minimum of a non-smooth
objective function using the Genetic Algorithm (GA) function in the
Genetic Algorithm and Direct Search Toolbox. Traditional derivative-based
optimization methods, like those found in the Optimization Toolbox, are
fast and accurate for many types of optimization problems. These methods
are designed to solve smooth , i.e., continuous and differentiable,
minimization problems, as they use derivatives to determine the direction
of descent. While using derivatives makes these methods fast and
accurate, they often are not effective when problems lack smoothness,
e.g., problems with discontinuous, non-differentiable, or stochastic
objective functions. When faced with solving such non-smooth problems,
methods like the genetic algorithm or the more recently developed pattern
search methods, both found in the Genetic Algorithm and Direct Search
Toolbox, are effective alternatives.
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Size: 18432 |
Author: gao |
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Description: lp范数最小化求解的问题，关于压缩感知的最新文档-lp-norm minimization problem solving, perception of the latest documentation on the compression
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Size: 327680 |
Author: 高飞 |
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Description: Entropy minimization for shadow removal proce-Entropy minimization for shadow removal process
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Size: 2469888 |
Author: menosgrande |
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Description: 图像分割，Minimization of Region-Scalable Fitting Energy
for Image Segmentation-LBF_v0.1:
This code implements an improved algorithm slightly modified from the original LBF model in the above paper.
A desirable advantage of this improved version of LBF algorithm is that it is very robust to contour initialization.
Author: Chunming Li, all rights reserved
E-mail: li_chunming@hotmail.com
URL: http://www.engr.uconn.edu/~cmli/
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Size: 398336 |
Author: 孙文方 |
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Description: 李纯明最新实现的局部活动轮廓模型的图像分割，比CV模型方法好很多。包含所实现的论文Minimization of Region-Scalable Fitting Energy for Image Segmentation-Li Chunming latest realization of the local active contour model for image segmentation, much better than the CV model approach. The paper contains the realization of Minimization of Region-Scalable Fitting Energy for Image Segmentation
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Size: 3272704 |
Author: syjsyj |
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Description: 一个遗传算法的函数优化，求函数的最小值，matlab编写的程序-A genetic algorithm for function optimization, seeking the minimization, matlab program written
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Size: 1024 |
Author: zuodongsheng |
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