Search - derivative

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[AI-NN-PR] webinar_files DL : 0: 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.
Date : 2026-01-10 Size : 18kb User : gao
[AI-NN-PR] steerfilter DL : 0: Design and Use of Steerable Filters PAMI1991文章的代码，含有测试图像和demo，可运行-It implements a steerable Gaussian filter. This m-file can be used to evaluate the first directional derivative of an image, using the method outlined in: W. T. Freeman and E. H. Adelson, "The Design and Use of Steerable Filters", IEEE PAMI, 1991.
Date : 2026-01-10 Size : 330kb User : 李
[AI-NN-PR] jixieshou DL : 0: ：本文提出了一种基于单纯形方法的机械手位姿逆解的分步求解方法。这种方法充分利用了单纯形法大范围收敛和计算简单的特性，在不计算目标函数一阶导数的情况下，确定极值点的查找方向与步长，多次迭代，直至目标函数满足所给条件。最后，用一个六自由度的肘机器人验证了该求解方法的有效性。- This paper presents a simplex method based on robot position and orientation of the sub-step inverse solution method. This method takes advantage of a wide range of simplex method convergence and easy to compute the characteristics of the objective function without calculating the first derivative of the situation, determine the extreme point to find the direction and step length, multiple iterations, until the objective function to meet the given the conditions. Finally, a six-degree of freedom elbow robot validate the solution method.
Date : 2026-01-10 Size : 751kb User : 杨元龙
[AI-NN-PR] BP DL : 0: 人工神经网络的C语言实现，程序涉及梯度下降法，函数求逆及偏导数的实现-Artificial Neural Networks C-language implementation, the program involves gradient descent method, function inverse and the partial derivative of the realization of
Date : 2026-01-10 Size : 2kb User : 赵新宇
[AI-NN-PR] ddt DL : 0: 微分方法方程 Calculate time derivative as a function of state and input variables of a (nonlinear) dynamic system - Calculate time derivative as a function of state and input variables of a (nonlinear) dynamic system
Date : 2026-01-10 Size : 2kb User : 张文荣
[AI-NN-PR] xdcau DL : 0: 该函数用来计算任意函数的一阶偏导数(数值方法),用平面波展开法计算二维声子晶体带隙,基于互功率谱的时延估计。- This function is used to calculate the arbitrary function of the first order partial derivative (numerical methods), Computation Method D phononic bandgap plane wave, Based on the time delay estimation of power spectrum.
Date : 2026-01-10 Size : 4kb User : 付平宝
[AI-NN-PR] fui-V2.1 DL : 0: 三相光伏逆变并网的仿真，该函数用来计算任意函数的一阶偏导数(数值方法),利用贝叶斯原理估计混合logit模型的参数。- Three-phase photovoltaic inverter and network simulation, This function is used to calculate the arbitrary function of the first order partial derivative (numerical methods), Bayesian parameter estimation principle mixed logit model.
Date : 2026-01-10 Size : 8kb User : 朱冬跃
[AI-NN-PR] 卷积神经网络 DL : 0: 建立卷积神经网络；使用训练样本对卷积神经网络进行训练；使用测试样本对卷积神经网络进行测试；卷积神经网络的前向计算过程；计算目标函数值，以及目标函数对权值和偏置的偏导数；更新网络的权值和偏置。(A convolutional neural network; convolutional neural network is trained using the training samples; test the convolutional neural network using the test sample; convolutional neural network prior to the calculation process; calculating the objective function value, and the objective function of the weights and bias of the partial derivative; more new network weights and bias.)
Date : 2026-01-10 Size : 5kb User : 涛声袅袅
[AI-NN-PR] generative-models-master DL : 1: 生成对抗网络中的各种衍生网络结构，包括基础GAN，C-GAN,AC-GAN等等变分自动编码器各种衍生网络结构，包括条件变分自动编码器等等(Generated in the network against the derivative network structure, including GAN, C-GAN, AC-GAN and so on. The variational autocoder derivative network structure, including conditional variational autocoder etc.)
Date : 2026-01-10 Size : 77kb User : 麦兜@@