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kalman-filtering-algorithm
卡尔曼滤波的源代码，里面包括了权向量的计算以及MSE的偏差曲线(Kalman filtering of the source code, which includes the calculation of the weight vector and the MSE deviation curve)
- 2011-06-27 11:57:01下载
- 积分：1
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symbolrate_estimation_cycle_MFSK
波特率估计算法，盲信号处里当中很重要的参数估计方法，本算法适合MFSK的波特率估计(estimation of baudrate)
- 2013-11-08 22:48:54下载
- 积分：1
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Digital-beam-forming
画出下述情况下均匀线阵方向图
1）计算来波方向为0度方向图
2）画出来波方向为45度时的方向图
3）画出来波方向为0度，幅度取分贝数：20log***（单位为dB）时的方向图
4）画出来波方向为0度，随着阵元数的增加，当N=16，N=32时的方向图，并对方向图的变化情况进行说明(Draw the following conditions uniform linear array
1) calculation of wave direction is 0 degrees direction diagram
2) draw out the wave direction is 45 degrees direction map
3) draw out the wave direction is 0 degrees, and amplitude decibels: 20log*** (unit dB) when the direction of FIG.
4) draw out the wave direction is 0 degrees, with the increase of the number of array elements, when N=16, N=32 pattern, and the change of direction is described
)
- 2013-05-02 23:44:17下载
- 积分：1
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jenqou_v54
通过虚拟阵元进行DOA估计，非归零型差分相位调制信号建模与仿真分析 ，用谱方法计算流体力学一些流动现象的整体稳定性。( Conducted through virtual array DOA estimation, NRZ type differential phase modulation signal modeling and simulation analysis, Spectral methods of computational fluid dynamics flow of some of the overall stability of the phenomenon.)
- 2016-05-09 14:01:41下载
- 积分：1
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8psk
8psk的仿真源码,有说明和解释,相关程序和函数都有.(8PSK simulation source, there are descriptions and explanations related to procedures and functions are.)
- 2008-06-14 15:54:28下载
- 积分：1
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Binary-Knapsack-Problem
the binary knapsack problem in matlab
- 2015-04-10 16:09:48下载
- 积分：1
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Mapping-General-Elastic-Coefficient
基于映射广义弹性系数的电网静态稳定快速评估判据(Rapid Quantitative Method for Power System Static Stability Assessment Based on
Mapping General Elastic Coefficient)
- 2016-11-04 20:16:14下载
- 积分：1
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calcError
Sensoer code is realted to loacalization that is written in matlab programming..
- 2009-07-09 01:36:25下载
- 积分：1
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multi-project1
INA controller for uav
- 2011-09-20 13:54:43下载
- 积分：1
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LMS
1,、设置变量和参量：
X(n)为输入向量，或称为训练样本
W(n)为权值向量
e(n)为偏差
d(n)为期望输出
y(n)为实际输出
η为学习速率
n为迭代次数
2、初始化，赋给w(0)各一个较小的随机非零值，令n=0
3、对于一组输入样本x(n)和对应的期望输出d，计算
e(n)=d(n)-X^T(n)W(n)
W(n+1)=W(n)+ηX(n)e(n)
4、判断是否满足条件，若满足算法结束，若否n增加1，转入第3步继续执行(, set the variables and parameters:
X (n) is the input vector, otherwise known as the training sample
W (n) for the weight vector
e (n) for the deviation
d (n) is the desired output
y (n) is the actual output
η is the learning rate
n is the number of iterations)
- 2011-12-10 20:22:05下载
- 积分：1
