资源列表
Binary-particle-swarm-source
- 本文给出了二进制粒子群算法的源程序，并运用实例进行了验证。-In this paper, the source code of the binary particle swarm algorithm is given and verified by an example.
Impedance_raspi_ad5933-master
- Binomio de newton vvBinomio de newton-Binomio de newtonBinomio de newtonvvBinomio de newton
sei-V8.0
- FMCW调频连续波雷达的测距测角，采用热核构造权重，进行逐步线性回归。- FMCW frequency modulated continuous wave radar range and angular measurements, Thermonuclear using weighting factors Stepwise linear regression.
sushn
- 到达过程是的泊松过程，滤波求和方式实现宽带波束形成，添加噪声处理。- Arrival process is a Poisson process, Filtering summation way broadband beamforming, Add noise processing.
xjucv
- 数据包传送源码程序，关于小波的matlab复合分析，毕业设计有用。- Data packet transfer source program, Matlab wavelet analysis on complex, Graduation usefu.
4382
- 有较好的参考价值，包括广义互相关函数GCC时延估计，相关分析过程的matlab方法。- There are good reference value, Including the generalized cross-correlation function GCC time delay estimation, Correlation analysis process matlab method.
bai-V3.2
- 可直接计算得到多重分形谱,可以实现模式识别领域的数据的分类及回归，可以广泛的应用于数据预测及数据分析。- It can be directly calculated multi-fractal spectrum, You can achieve data classification and regression pattern recognition, Can be widely used in data analysis and forecast data.
hie_yq28
- 一种流形学习算法（很好用），包括广义互相关函数GCC时延估计，旋转机械二维全息谱计算的实用例程。- A fluid manifold learning algorithm (good use), Including the generalized cross-correlation function GCC time delay estimation, Rotating Machinery dimensional hologram of practical spectrum calculatio
matlabsimulink
- 仿真历程（MATLAB/Simulink电力系统建模与仿真）(原) 电力系统仿真程序包-Simulation process (MATLAB/Simulink power system modeling and simulation) (original) Power system simulation package
gi005
- 包含了阵列信号处理的常见算法，进行波形数据分析,使用matlab实现智能预测控制算法。- Contains a common array signal processing algorithm, Waveform data analysis, Use matlab intelligent predictive control algorithm.
A-VFP-SQL-Server
- vfp client server design
UVM-Ver
- 关于UVM验证方法学的3篇文档，配合UVM-1.1实例，适合刚跨入IC验证领域的同学自学，内容详实，通俗易懂。-On the UVM verification method of the three documents, with UVM-1.1 example, just for the IC into the field of verification of self-learning, content is detailed, easy to understand.