-
DSP
DFT 计算
实验步骤：
主界面下进入实验九的“DFT计算”的子实验。
输入取样点数，即有限长序列 x(n) 的长度。
输入信号表达式，或直接输入离散序列。
鼠标单击确定按钮，显示原序列及 DFT 系数的幅度、相位。(DFT calculation of the experimental steps: the main interface into the experimental Kau " DFT calculation of" sub-experiment. Enter the sampling points, that is, finite sequences x (n) length. Expression of the input signal, or directly onto a discrete sequence. Mouse click OK button to display the original sequence and the magnitude of DFT coefficients, phase.)
- 2009-05-01 20:41:59下载
- 积分：1
-
GPS-CAcode
GPS信号C／A码生成算法设计及仿真实现,pdf
格式的参考论文(GPS signal C/A Code Generation Algorithm Design and Simulation, pdf format of the reference paper)
- 2011-05-31 11:17:20下载
- 积分：1
-
inline-lsqcurvefit-matlab-code
Matlab inline-lsqcurvefit 参数拟合例子的源代码(Matlab inline-lsqcurvefit parameter fitting examples of source code)
- 2013-09-05 14:58:12下载
- 积分：1
-
extend-dft
扩展功能的DFT，可以自动扩展输入序列X，如果你输入的长度不足N，会自动以NaN补足(Extension of the DFT, can be automatically extended input sequence X, if you enter a length less than N, will automatically fill in NaN)
- 2011-11-21 22:06:39下载
- 积分：1
-
FDC-6DOF
6 DOF EOM Solved for Aircraft
- 2011-12-02 18:57:11下载
- 积分：1
-
Audio-Processing
音频系统，coding, modulation, AWGN, 通过最小距离探测码元，解码，播放。根据不同的SNR，测试在多小的SNR情况下，人耳能识别音频。(Audio systems, coding, modulation, AWGN, by minimizing the distance detection symbol, decoding, playing. Depending on the SNR, the test in the case of multiple small SNR, the human ear can identify audio.)
- 2014-02-20 02:58:39下载
- 积分：1
-
NeuralNetwork_BP_Regression
NeuralNetwork_BP_Regression.m - 回归(NeuralNetwork_BP_Regression.m- Regression)
- 2009-03-07 16:29:51下载
- 积分：1
-
MATLAB_shipoqi
一个简单的图形用户界面，演示了从示波器如何检索和显示数据。(A simple graphical user interface, presentation on how to retrieve and display data from the oscilloscope.)
- 2012-07-14 11:16:11下载
- 积分：1
-
RHandRand
用matlab仿真对光谱进行定标和很好的一个随机数发生器(Matlab simulation of the spectrum used for calibration and a very good random number generator)
- 2009-04-04 13:21:54下载
- 积分：1
-
kaerman
说明： 实现卡尔曼滤波，可以看出，滤波过程是以不断地“预测—修正”的递推方式进行计算，先进行预测值计算，再根据观测值得到的新信息和kalman 增益（加权项），对预测值进行修正。由滤波值可以得到预测，又由预测可以得到滤波，其滤波和预测相互作用，并不要求存储任何观测数据，可以进行实时处理。(Kalman filtering, can be seen, the filtering process is constantly " forecast- Fixed" recursive manner calculated to predict the value of the first, and then according to the new information should be observed and the kalman gain (weighted items), on predictive value of the amendment. Value can be predicted by the filter, but also can be filtered by the forecast, and its interaction filtering and prediction, does not require the storage of any observational data, real-time processing.)
- 2011-02-27 10:33:13下载
- 积分：1
