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xxt
用C编写的地震资料楔形体模型，可以变换参数，简单通用(Written using C seismic data wedge model, may come and go parameters, simple and universal)
- 2010-07-14 09:38:00下载
- 积分：1
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LensDesign
this is a lens designing book
- 2009-05-08 12:54:42下载
- 积分：1
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matlab20and20BP
for load forecasting paper
- 2008-05-22 14:27:27下载
- 积分：1
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hibernate_annotation
hinbernate的练习适合新手的学习和使用。(Three practical feasibility of SSH framework)
- 2015-03-04 19:18:07下载
- 积分：1
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aero_gen
aerogenerator model for wind turbine
- 2010-10-05 20:40:36下载
- 积分：1
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Abstract
it s a communication document
- 2014-11-15 15:00:56下载
- 积分：1
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popfnn
说明： popfnn神经网络，它是一种模糊伪输出的神经网络(pseudo-outer-production fuzzy nerual network).可用于模式识别。运行pop1可以训练输入的特征向量，extractionpop使用来抽取图片的特征向量的。(popfnn neural network, it is a pseudo-output fuzzy neural network (pseudo-outer-production fuzzy nerual network). can be used for pattern recognition. Can be trained to run pop1 input feature vector, extractionpop used to extract the image feature vector.)
- 2010-04-21 21:28:23下载
- 积分：1
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OFDM-simulation
QAM和OFDM两种方式性能对比，具有图形界面GUI，并且包括收发两端完成的代码
(QAM and OFDM performance comparison of two ways, with a graphical interface GUI, and includes the sending and receiving ends to complete the code)
- 2013-11-29 20:01:24下载
- 积分：1
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dip2
说明： 基于信息融合的图像边缘检测方法研究,⑴直方图均衡化（histogram equalization），⑵直方图匹配（histogram matching），⑶邻域平均（neighborhood averaging），⑷局域增强（local enhancement）， ⑸中值滤波（median filtering）。(Edge detection method, 1 histogram equalization (histogram equalization). 2 histogram matching (histogram matching). 3 Neighborhood average (neighborhood averaging) 4 Local Enhancement (local enhancement). together median filter (median filtering).)
- 2006-05-14 17:16:31下载
- 积分：1
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ECG
The early detection of arrhythmia is very important
for the cardiac patients. This is done by analyzing the
electrocardiogram (ECG) signals and extracting some features
from them. These features can be used in the classification of
different types of arrhythmias. In this paper, we present three
different algorithms of features extraction: Fourier transform
(FFT), Autoregressive modeling (AR), and Principal Component
Analysis (PCA). The used classifier will be Artificial Neural
Networks (ANN). We observed that the system that depends on
the PCA features give the highest accuracy. The proposed
techniques deal with the whole 3 second intervals of the training
and testing data. We reached the accuracy of 92.7083
compared to 84.4 for the reference that work on a similar
data.
- 2011-09-22 19:15:10下载
- 积分：1
