Description: 目标函数是De Jong函数，是一个连续、凸起的单峰函数-Objective function is De Jong function, is a continuous, convex function of the single-peak Platform: |
Size: 2048 |
Author:齐乐 |
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Description: Designs a frequency-domain and time-domain FIR equalizer for
a single-input single-output (SISO) channel.
Frequency-domain equalization uses a Chebychev criteria and
is specified in terms of frequency response functions.
It is a convex problem (which can be formulated as an SOCP):
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where H is the frequency response function and our variable
is the filter impulse response h. Function G is the unequalized
frequency response and G_des is the desired freq response.
Time-domain equalization immediately designs the impulse
response function by specifying the problem in time (it s an LP):
minimize max_{t neq D} |g_tilde(t)|
s.t. g_tilde(D) = 1
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Size: 1024 |
Author:wwcj |
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Description: The Rosenbrock function is a non-convex function used as a performance test problem for optimization algorithms introduced by Rosenbrock (1960). It is also known as Rosenbrock s valley or Rosenbrock s banana function.
The global minimum is inside a long, narrow, parabolic shaped flat valley. To find the valley is trivial. To converge to the global minimum, however, is difficult. Platform: |
Size: 1024 |
Author:suci ariani |
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Description: this matlab code that perform convex optimization for several objective function types-this is matlab code that perform convex optimization for several objective function types Platform: |
Size: 7168 |
Author:shadaaa |
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Description: 多面体凸集的函数下载之后加到MATLAB中就可以用了-Function of polyhedral convex set after download added to the MATLAB can be used Platform: |
Size: 11264 |
Author:husuqiang |
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Description: 该程序能够实现对于一个样本完成感知机，最小二乘法，凸优化方法解决SVM和matlab自带函数解决SVM的四种程序，并且通过修改部分参数可以完成不同效果。(The program can be achieved for a complete sample perceptron, least squares method, convex optimization method to solve SVM and MATLAB with four program function to solve the SVM, and by modifying some parameters can achieve different effects.) Platform: |
Size: 14336 |
Author:围生
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Description: 用于稀疏优化的最新非凸函数GMC算法，可用于信号处理以及图像处理。(The latest non convex function GMC algorithm for sparse optimization, can be used for signal processing and image processing.) Platform: |
Size: 417792 |
Author:A_sponge
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Description: 梯度下降法是最早最简单，也是最为常用的最优化方法。梯度下降法实现简单，当目标函数是凸函数时，梯度下降法的解是全局解。一般情况下，其解不保证是全局最优解，梯度下降法的速度也未必是最快的。梯度下降法的优化思想是用当前位置负梯度方向作为搜索方向，因为该方向为当前位置的最快下降方向，所以也被称为是”最速下降法“。最速下降法越接近目标值，步长越小，前进越慢。(The gradient descent method is the earliest and most simple and most commonly used optimization method. The gradient descent method is simple to realize. When the objective function is a convex function, the solution of the gradient descent method is a global solution. In general, the solution is not guaranteed to be the global optimal solution, and the gradient descent method is not necessarily the fastest. The optimization idea of gradient descent method is to use the current position negative gradient direction as the search direction, because the direction is the fastest descending direction of the current position, so it is also called the steepest descent method. The faster the slowest descent approach is closer to the target, the smaller the step, the slower the progress.) Platform: |
Size: 3072 |
Author:hxxa |
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