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shenjingwangluo
说明： 使用HOPfield神经网络求解参数线性约束规划，此代码为原创，可直接运行。(Use HOPfield Neural networks for solving parametric linear constrained programming, the code for the original, can be directly run.)
- 2010-03-31 20:24:08下载
- 积分：1
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PSO
粒子群算法，用于函数优化问题，也可以求得最短路等问题。(Particle Swarm Optimization)
- 2011-08-21 23:09:33下载
- 积分：1
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harris_ncc
harris角点检测，并对检测的角点用NCC进行匹配(harris corner detection, and detection of the corner points are matched with NCC)
- 2013-07-20 16:02:39下载
- 积分：1
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bhm
谐波平衡法计算非线性微分方程，十分好用。简单方便。(HBM method)
- 2015-07-10 17:31:03下载
- 积分：1
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Modi_Gram_S
modified Gram-Schmidt (reduced QR factorization). A is a m-by-n matrix(m>=n)
- 2021-02-22 10:59:41下载
- 积分：1
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trainE
Least mean squares (LMS) algorithms is a type of adaptive filter used to mimic a desired filter by finding the filter coefficients that relate to producing the least mean squares of the error signal (difference between the desired and the actual signal)
- 2010-05-07 00:04:14下载
- 积分：1
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tx
说明： matlab sdr model works awesome
- 2012-04-12 20:58:50下载
- 积分：1
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PLS
这是很全面偏最小二乘法程序,并且具有中文注释，有效帮助大家利用PLS算法。(It is program of Partial least square.It is noted by chinese.)
- 2010-06-02 15:07:53下载
- 积分：1
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QR_Decomposition
QR Decomposition for non quadratic system
- 2011-01-13 05:25:24下载
- 积分：1
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New-Text-Document-(2)
he form of the Burgers equation considered here is:
du du d^2 u
-- + u * -- = nu * -----
dt dx dx^2
for -1.0 < x < +1.0, and 0.0 < t.
Initial conditions are u(x,0) = - sin(pi*x). Boundary conditions are u(-1,t) = u(+1,t) = 0. The viscosity parameter nu is taken to be 0.01 / pi, although this is not essential.
The authors note an integral representation for the solution u(x,t), and present a better version of the formula that is amenable to approximation using Hermite quadrature.
This program library does little more than evaluate the exact solution at a user-specified set of points, using the quadrature rule. Internally, the order of this quadrature rule is set to 8, but the user can easily modify this value if greater accuracy is desired.
- 2012-04-13 12:06:48下载
- 积分：1
