-
gauseidel.matlab
求线性方程组的迭代法(高斯赛德尔)，基于MATLAB开发(Linear Iterative Method (high Sisaideer))
- 2010-12-13 17:28:26下载
- 积分：1
-
BeamFormer
说明： 一个在智能天线技术里的波束形成算法(A smart antenna technology in the beamforming algorithm)
- 2008-10-10 20:53:03下载
- 积分：1
-
ofdm
这是ofdm的MATLAB仿真源程序，很好用(This is the MATLAB simulation ofdm source, useful)
- 2010-08-25 22:12:03下载
- 积分：1
-
Matlab
这个文件是，opendss与matlab交互编程的标准示例，可以帮助学习者更快的掌握opendss与matlab的交互(This file is a standard example opendss interact with matlab programming, can help learners to quickly grasp the interaction with the matlab opendss)
- 2013-12-16 23:21:39下载
- 积分：1
-
Real-codedGA
用MATLAB分别采用浮点编码和二进制编码方法，求函数最大值的程序。(were used with MATLAB floating-point code and binary coding method, the maximum function for the procedure.)
- 2006-10-28 17:25:34下载
- 积分：1
-
kpca
运用KPCA方法在ORL人脸库上进行人脸识别，分类器为最近邻分类器。(KPCA method using ORL face database for face recognition, classification for the nearest neighbor classifier.)
- 2010-12-01 14:14:25下载
- 积分：1
-
G1
说明： this program for SMIB with statcom to damp power system stabil ity
- 2013-01-12 02:50:13下载
- 积分：1
-
DTproTest
DTproTest滴水动态变形-飘功能例子.rar(DTproTest example DTproTest example)
- 2015-02-02 01:49:55下载
- 积分：1
-
QRDCMP
用镜像矩阵求出矩阵的QR分解（正交三角分解），并求解线性方程组，该方法不必选主元，但其计算过程非常稳定。也可用于求矩阵的广义逆和求解线性最小二乘问题。子过程QRDCMP用镜像矩阵求m*n矩阵A的QR分解，A=Q^TR,其中Q是m*m正交矩阵，R为m*n上三角矩阵；子过程QRBKSB用矩阵的QR分解求解线性方程组Ax=b，其中A为n阶非奇异方阵。(Matrix obtained with the mirror matrix QR decomposition (orthogonal triangular decomposition), and solving linear equations, the method does not have to choose the main element, but its calculation process is very stable. Can also be used to find the generalized inverse matrix and solving linear least squares problems. Sub-process of the mirror matrix QRDCMP m* n matrix A QR decomposition, A = Q ^ TR, wherein Q is a m* m orthogonal matrix, R is m* n upper triangular matrix subprocess QRBKSB a QR decomposition to solve the matrix linear equations Ax = b, where A is non-singular square matrix of order n.)
- 2013-09-27 11:05:18下载
- 积分：1
-
Body-Area-Networks
一个身体部位比较模型的新方法网络（BAN）的，可以容纳多个环节和多个科目。所述的绝对测量允许跨频谱可能刻画的比较 从单参数为整个合奏，通过基于参数化到每个活动，每个学科和每个环节模型。使用错误，并明确之间权衡复杂性，在一个善良的适应措施相结合，显示有重要的影响时，适用于一系列典型的禁止通道数据。它是有不同的
在模式的选择的影响，以及它相关的复杂性，混合活动的“日常”的数据，设置活动相比，动态数据（例如步行）。平均路径损耗的不足，甚至位数的路径损失的措施，作为唯一的表征还强调“禁止通道。
(A new approach to compare models for body area
networks (BAN) that accommodates multiple links and multiple
subjects is presented. The absolute measure described allows
comparison across a spectrum of possible characterizations
ranging from single-parameter for an entire ensemble, through
to per-activity, per-subject and per-link based parameterized
models. The use of an explicit trade-off between error and
complexity, combined in a goodness-of-fit measure, is shown
to have important consequences when applied to a range of
typical BAN channel data. It is shown that there are different
implications in choice of model, and it’s associated complexity, for
mixed-activity “everyday” data, when compared with set-activity
dynamic data (e.g. walking). The deficiency of mean path loss,
or even median path loss measures, as a sole characterization of
the BAN channel is also highlighted.)
- 2011-12-01 21:21:32下载
- 积分：1
