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Burgers
用麦克麦考方法求解一维burgers方程的matlab代码(By Mike McCaw method for solving one-dimensional burgers equation matlab code)
- 2021-02-13 14:59:49下载
- 积分：1
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nijie
六轴工业机器人的逆运动学,采用VC++进行编程自动求解(inverse of 6-dof industrial robot)
- 2020-12-25 12:19:04下载
- 积分：1
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3107002005_2nd_A_LDL
说明： LDL分解。作为矩阵方程数值解法最基础的矩阵分解算法，LDL算法可以高效分解对称矩阵。(LDL decomposition. Numerical Solution of matrix equation as the most basic matrix factorization algorithm, LDL decomposition algorithm can be efficient symmetric matrix.)
- 2008-10-27 10:47:26下载
- 积分：1
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hope
变步长网格，声波方程，有限差分数值模拟程序，二阶(Variable step mesh, acoustic equation, finite difference numerical simulation program, second order)
- 2016-11-04 14:38:13下载
- 积分：1
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program3
早期的圆柱绕流程序，用fortran语言编写，用来了解早期绕流流动的发展(flow around the cylinder)
- 2011-06-22 16:06:03下载
- 积分：1
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fftAna
FFT（Fast Fourier Transformation）是离散傅氏变换（DFT）的快速算法 [1] 。即为快速傅氏变换。它是根据离散傅氏变换的奇、偶、虚、实等特性，对离散傅立叶变换的算法进行改进获得的。(FFT (Fast Fourier Transform) is a fast algorithm of discrete Fourier Transform (DFT). That is fast Fourier transform. According to the odd, even, imaginary and real characteristics of discrete Fourier transform, the algorithm of discrete Fourier transform is improved.)
- 2020-06-21 06:00:02下载
- 积分：1
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least_squares_phase_unwrapping_algorithm
详细讨论了INSAR技术中相位解缠最小二乘方法的算法实现；并提出改进的加权最小二乘算法的实现思路(INSAR techniques are discussed in detail in the method of least squares phase unwrapping algorithm and suggestions for improvement of the weighted least squares algorithm implementation ideas)
- 2020-06-29 07:20:01下载
- 积分：1
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fft
计算fft，输出频谱，相位，模值,Calculation of FFT, the output frequency, phase, amplitude,
- 2021-03-05 15:29:32下载
- 积分：1
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HartleyTransform
The Fast Hartley Transform (FHT) implementation.
- 2011-05-24 21:39:11下载
- 积分：1
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ADAM
说明： ADAM （Adaptive Moment Estimation）是另外一种自适应学习率算法，它结合动量梯度
下降法，在不同参数方向上采用不同学习率，保留前几次迭代的梯度，能够很好
的适应于稀疏数据。(ADAM (Adaptive Moment Estimation) is another adaptive learning rate algorithm, which combines momentum gradient.
The descent method, which uses different learning rates in different parameter directions and retains the gradients of previous iterations, is very good.
It is suitable for sparse data.)
- 2019-04-09 19:59:50下载
- 积分：1
