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TUTORIAL
说明： 几个网络的生成程序度，度分布，聚类数
(some net matlab show，degree degreedistrict)
- 2010-04-02 12:48:36下载
- 积分：1
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xindaorongliangbianma
信道容量编码，C语言实现，照着程序一步一步做会找到你需要的(Channel capacity coding, C language, according to the program will find step by step what you need to do)
- 2014-01-09 11:04:49下载
- 积分：1
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nnv
包括回归分析和概率统计，FIR 底通和带通滤波器和IIR 底通和带通滤波器，包括最小二乘法、SVM、神经网络、1_k近邻法,D-S证据理论数据融合，保证准确无误，是学习通信的好帮手，关于神经网络控制，FMCW调频连续波雷达的测距测角。( Including regression analysis and probability and statistics, Bottom-pass and band-pass FIR and IIR filter bottom pass and band-pass filter, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, D-S evidence theory data fusion, Ensure accurate communication is learning a good helper, On neural network control, FMCW frequency modulated continuous wave radar range and angular measurements.)
- 2016-04-14 15:37:08下载
- 积分：1
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electrical-machinery-simulation
DYNAMIC SIMULATION OF ELECTRIC MACHINERY by Chee-Mun Ong,
published by Prentice-Hall
- 2013-07-10 14:15:38下载
- 积分：1
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LTE-packet
In Modulation schemes such as OFDM transmitter time domain signal will have higher PAPR, which leads to various distortions in the transmitter chain and degradation of system performance i.e. BER/PER. Also requires highly linear power amplifier which increases cost of the system. PAPR is ratio of peak power to average power of time domain complex baseband signal which is to be transmitted. We will discuss PAPR reduction techniques below.
- 2014-12-19 13:13:55下载
- 积分：1
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005_JSaCR-master
说明： 基于空间感知的协同表示算法应用于高光谱遥感图像分类(Spatial-Aware Collaborative Representation for Hyperspectral Remote Sensing Image Classification)
- 2019-10-31 09:51:04下载
- 积分：1
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clock
用matlab做的立体时钟，可以使一个很好的东西，显示当前时间(clock done with matlab)
- 2009-10-12 19:41:12下载
- 积分：1
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Desktop
MATLAB实现（7，4）汉明码编码 生成矩阵可以更改有注释 方便更改(MATLAB implementation (7,4) hamming code generator matrix can be changed easily to change a comment)
- 2010-12-25 10:22:17下载
- 积分：1
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fit_ML_maxwell
fit_ML_normal - Maximum Likelihood fit of the log-normal distribution of i.i.d. samples!.
Given the samples of a log-normal distribution, the PDF parameter is found
fits data to the probability of the form:
p(x) = sqrt(1/(2*pi))/(s*x)*exp(- (log(x-m)^2)/(2*s^2))
with parameters: m,s
format: result = fit_ML_log_normal( x,hAx )
input: x - vector, samples with log-normal distribution to be parameterized
hAx - handle of an axis, on which the fitted distribution is plotted
if h is given empty, a figure is created.
output: result - structure with the fields
m,s - fitted parameters
CRB_m,CRB_s - Cram?r-Rao Bound for the estimator value
RMS - RMS error of the estimation
type - ML
- 2011-02-09 19:08:34下载
- 积分：1
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lab1_discussion_question
DSP course lab1_discussion_question
- 2011-11-07 23:45:55下载
- 积分：1
