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xindaojunheng
信道的频率响应是时变的,设计最佳的固定的解调滤波是不可能的,因此,需要一种能补偿或减少接收信号中ISI的方法,这种ISI补偿方法称为均衡方法。
自适应均衡技术能够用来抵消由于信道带限或时间色散所导致的码间干扰,可以使通信系统更有效地利用信道带宽。
(Channel frequency response is time-varying, the best fixed design demodulation filter is impossible, therefore, need to be able to receive compensation or reduce the signal in the ISI method, the ISI compensation is called a balanced approach. Adaptive equalization techniques can be used to offset the channel band-limited or time dispersion caused by the inter-symbol interference can make communication systems more efficient use of channel bandwidth.)
- 2011-09-26 17:54:36下载
- 积分:1
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RDGT
实值离散gabor matlab 代码。来源于实值离散gabor经典书籍。(Real-valued discrete gabor matlab code)
- 2011-11-09 21:15:02下载
- 积分:1
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27413685VBLAST
V-BLAST MIMO STRUCTURE
- 2011-11-16 03:43:39下载
- 积分:1
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Mandelbrot_Fractal_Matlab
this is mandelbrot fractal matlab code
- 2012-10-02 14:06:14下载
- 积分:1
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jiumeng
验证可用,基于欧几里得距离的聚类分析,小波包分析提取振动信号中的特征频率。( Verification is available, Clustering analysis based on Euclidean distance, Wavelet packet analysis to extract vibration signal characteristic frequency.)
- 2016-09-06 17:56:55下载
- 积分:1
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Circuit_Analysis_II_with_MATLAB
Circuit Analysis II with MATLAB
- 2009-05-01 20:57:41下载
- 积分:1
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picshibie
实现了图像识别的matlab程序,可以直接使用,里面有例子,适合新手学习(To achieve the image recognition matlab program can be used directly, which there are examples, suitable for novice to learn)
- 2009-12-14 15:11:00下载
- 积分:1
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BilinearSystems
concerned with the blind identication of
bilinear systems excited by higher-order white noise. Un-
like prior work that restricted the bilinear system model to
simple forms and required the excitation to be Gaussian dis-
tributed, the results of this paper are applicable to a more
general class of bilinear systems and for the case when the
excitation is non-Gaussian. We describe an estimation pro-
cedure for the computation of the system parameters using
output cumulants of order less than four.
- 2009-05-26 22:19:50下载
- 积分:1
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optics
optics算法 [RD,CD,order]=optics(x,k); Aim: Ordering objects of a data set to obtain the clustering structure
Input: x - data set (m,n) m-objects 对象数, n-variables 变量数
k - number of objects in a neighborhood of the selected object(OPTICS Ordering Points To Identify the Clustering Structure)
- 2012-07-17 22:49:29下载
- 积分:1
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seisemic_zhejihecheng
地球物理地震数据处理,专用于卷积合成卷积(Geophysical seismic data processing, convolution)
- 2013-12-30 07:11:36下载
- 积分:1