-
RSNA
待辨识对象参数a=[1 -1.5 0.7] b=[1 0.5] 输入采用长度L=400的白噪声序列，输出 ，输入和输出数据均含不相关随机噪声，ρ（k）=1/k。利用上述递推公式，辨识系统参数。(To identify the object parameters a = [1-1.5 0.7] B = [1 0.5] Input the length L = 400 white noise sequence, the output, the input and output data are not related with random noise, ρ (k) = 1/k. Using the recursion formula, identification system parameters.)
- 2012-12-28 16:21:16下载
- 积分：1
-
matlab
Matlab命令速查Word版，对初学者英语不好者可以有点帮助(Matlab Command Quick Word version of English is not good for beginners who can help a little)
- 2011-08-15 22:38:33下载
- 积分：1
-
icml09-deepbeliefnetwork
相比DeconvNet写得比较简洁易懂。但是原来代码里面给的数据似乎没法跑。所幸同作者还有一些代码用到了TCNN，比如action recognition，可以一起下载下来参考。这个代码主要特色就是tiled结构，可以用来参考，然后把里面ICA的优化函数换成RICA，Sparse Coding等等。总之，在这个代码里也了解了不少(比如line search等)。(DeconvNet well written and easy to understand compared to relatively simple. But the original code to the data inside can not seem to run. Fortunately, there are some code with the author uses TCNN, such action recognition, can be downloaded along down the reference. This code is the main feature tiled structure that can be used for reference, and then put inside the ICA optimization functions into RICA, Sparse Coding and so on. In short, this code can also learn a lot (such as line search, etc.).)
- 2015-01-16 16:08:59下载
- 积分：1
-
mmse_diedai08
最佳权向量自适应迭代更新MSE对比波形，内有详细说明，供大家参考。(optimal weight vector adaptive waveform update MSE contrast, with detailed notes for reference.)
- 2007-06-05 01:30:31下载
- 积分：1
-
qushichanliang
用直线滑动平均法计算趋势产量，步长为11。(The linear sliding average method trend yield step 11.)
- 2021-04-08 17:19:00下载
- 积分：1
-
Vertical_well_Q_steady
这是一个Matlab源码，用于计算直井稳定产能(Steady productivity of vertical wells)
- 2014-02-24 11:53:22下载
- 积分：1
-
matlab
陈仲生 《基于matlab7.0的统计信息处理》(陈仲生" matlab7.0 based on statistical information processing" )
- 2009-06-06 01:13:04下载
- 积分：1
-
no_channelcode_QAM_gausschannel
说明： 数据经过多进制QAM调制下，通过高斯信道的误码率比较(the rand data are modulated by MQAM ，then pass the gausschannel ，get the compared result of ber.)
- 2009-08-04 13:03:26下载
- 积分：1
-
development-risk-prediction
本文基于BP神经网络应用于预测的原理，提出预测步骤及预测可行性，探讨建立基于BP神经网络的预测模型的关键技术，包括样本的选取与预处理、输入输出变量的选取、隐层节点数的确定、初始权值和阈值的选取、激活函数、训练算法与参数的选取，最后建立合理的网络模型；结合住宅市场的实际情况，建立两类BP 神经网络预测模型：基于时间序列的趋势预测模型以及基于影响因素的回归预测模型，即分别采用神经网络趋势预测和回归预测的思路，把住宅市场的供给、需求与房价的历年数据以及其影响因素的数据分别作为学习样本，建立预测模型，进行预测。(Real estate development risk prediction
)
- 2011-04-22 10:40:30下载
- 积分：1
-
MATLABprogrammingCH01
這是一本MATLAB程式設計延伸技巧程式書本上的程式碼CH1(一次無法全部上傳會斷線)(This is an extension of MATLAB programming skills in program code books CH1)
- 2010-05-27 13:41:27下载
- 积分：1
