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ch1example3prg1
- 单摆运动过程的建模和仿真，忽略空气阻力因素-Pendulum movement of the modeling and simulation process, ignore the air resistance factor
makeLdpc
- LDPC编码算法, Create R = 1/2 low density parity check matrix M : Number of row N : Number of column method : Method for distributing non-zero element {0} Evencol : For each column, place 1s uniformly at random {1} Evenboth: For each
6spline
- 返回系数估计向量；stats返回各种参数估计；’wfun’指定一个加权函数；tune为调协常数；’const’的值为’on’(默认值)时添加一个常数项；为’off ’时忽略常数项-Return coefficient estimate vector stats back to a variety of parameter estimation ' wfun' to specify a weighting function tune for the co-ordination
Version_1p1_Final
- Reads TDMS files into Matlab. See TDMS_exampleFunctionCalls.m to get started. Advantages: - supports reading v2 files - doesn t require the NI DLL, thus it doesn t require 32bit windows - supports interleaved data - allows only r
RD
- SAR成像的算法很多，以上文件为简单易懂的条带SAE成像RD算法。忽略距离徙动和距离弯曲的影响。-Many SAR imaging algorithm , the above file with SAE imaging RD algorithm is simple and easy to understand article . Ignore the range migration and distance bending .
four
- 计算成组滑动的滑窗检测器的最佳门限已知: 击中数N = 128, 组宽n = 8，PF = 10¡ 6，PD = 90 假设以下条件: (a) 信号不起伏 (b) 忽略天线波束调制 1 (c) 计算PD时忽略目标区以外噪声的影响 组门限(第二门限)为K=8 滑窗的门限(第三门限)为L=16 (滑窗中包含的组数为16) 求解: 最佳的KOPT 和LOPT，对这题做了具体仿真实现。需要的朋友，一定知道很有用。-Optimal threshold calculate
NSGA-II
- NSGA是基于对个体的几层分级实现的。在选择执行 前,群体根据支配与非支配关系来排序:所有非支配个体被排成一类,这些被分级的个体共享它们的虚拟适应度值。然 后,忽略这组已分级的个体,对种群中的其它个体按照支配与非支配关系再进行分级,该过程继续直到群体中的所有个体被分级。(The NSGA is based on the individual layers of grading. Before selecting execution groups, according to govern with
nanmedfilt2
- 均值滤波时能够忽略NAN的影响 对于影像处理有比较好的速度(Mean filtering can ignore the effect of NAN)
SmoothingGraph34
- Another way to represent a polynomial is to use the Laplace variable s within MATLAB. This method is mainly used throughout these tutorials. Let's ignore the details of the Laplace domain for now and just represent polynomials with the s variable. To
sim
- Another way to represent a polynomial is to use the Laplace variable s within MATLAB. This method is mainly used throughout these tutorials. Let's ignore the details of the Laplace domain for now and just represent polynomials with the s variable. To