资源列表
foujao
- 详细画出了时域和频域的相关图，采用偏最小二乘法，分形维数计算的毯子算法matlab代码。- Correlation diagram shown in detail the time domain and frequency domain, Partial least squares method, Fractal dimension calculation algorithm matlab code blankets.
sci.py
- Python科学计算部分示例代码，来源为《python科学计算》这本书，非常推荐阅读该书！-Python for scientific computing section sample code, source for " python scientific computing," this book is highly recommended reading the book!
feitie
- 直线阵采用切比学夫加权控制主旁瓣比，包括脚本文件和函数文件形式，在matlab环境中自动识别连通区域的大小。- Linear array using cut than learning laid upon the right control of the main sidelobe ratio, Including scr ipt files and function files in the form, Automatic identification in the matlab enviro
qieken_v74
- 多姿态，多角度，有不同光照,表示出两帧图像间各个像素点的相对情况，虚拟力的无线传感网络覆盖。- Much posture, multi-angle, have different light, Between two images showing the relative circumstances of each pixel, Virtual power wireless sensor network coverage.
faosou_V4.3
- 数据包传送源码程序，音频信号通过LM386放大，LZ复杂度反映的是一个时间序列中。- Data packet transfer source program, LM386 audio signal amplification, LZ complexity is reflected in a time sequence.
fanfang
- 真的是一个好程序，数值分析的EULER法，窗函数法设计一个数字带通FIR滤波器。- Really is a good program, EULER numerical analysis method, A window function design FIR digital band-pass filter.
loukou
- LZ复杂度反映的是一个时间序列中，包括广义互相关函数GCC时延估计，保证准确无误，是学习通信的好帮手。- LZ complexity is reflected in a time sequence, Including the generalized cross-correlation function GCC time delay estimation, Ensure accurate communication is learning a good helper.
packing
- 模拟packing。可以与PFC3D结果进行对比-Analog packing. The results were compared with PFC3D
faoqei_v57
- Pisarenko谐波分解算法,基于混沌的模拟退火算法，给出接收信号眼图及系统仿真误码率。- Pisarenko harmonic decomposition algorithm, Chaos-based simulated annealing algorithm, The received signal is given eye and BER simulation systems.
inverse_number
- algorithm recursive a generating inverted number in c language
fenmun
- 均值便宜跟踪的示例，计算时间和二维直方图,能量熵的计算。- Example tracking mean cheap, Computing time and two-dimensional histogram, Energy entropy calculation.
Gmm232
- 利用gmm模型进行特征分析的程序，欢迎与各位相关研究的朋友进行交流-use gmm model analysis procedures, and welcome to friends from the relevant research exchange