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otsu
OTSU Gray-level image segmentation using Otsu s method.
Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes
by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection
Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern.
9:62-66 1979). Thresholds are computed to maximize a separability
criterion of the resultant classes in gray levels.
OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the
corresponding Iseg is therefore a binary image. The pixel values for
Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ...
[Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability
criterion within the range [0 1]. Zero is obtained only with images
having less than n gray level, whereas one (optimal value) is obtained
only with n-valued images.
- 2009-03-17 17:57:51下载
- 积分：1
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TheResearchofSpatialSpectrumEstimationAlgorithminS
智能天线技术是第三代移动通信系统的关键技术之一，也是国内外热门的研究课题。由于无线移动通信的信道传输环境具有复杂性和不确定性，存在多径衰落和时延扩展，因此造成了符号间串扰、同信道干扰、多址干扰等，这些干扰降低了链路性能和系统容量，智能天线技术是解决以上问题的方法之一。 本文首先阐述了智能天线和白适应波束形成的基本理论，然后对自适应算法进行了研究。对一些基本的自适应算法最小均方算法、恒模算法及递推最小均方算法进行了分析讨论，用计算机仿真的结果论证了算法的性能。针对相干干扰介绍了空间平滑技术，对传统的相干干扰抑制方法-空间平滑法进行了分析，采用改进算法有效降低了空间平滑算法的运算量。对信号波达方向(DOA)的估计是智能天线研究的另一关键问题。第四章在介绍了阵列信号处理方法的基础上，先简单介绍了Bartlett、Capon、MUSIC等空间谱估计算法，分析了信源数目过估计与欠估计情况下的MUSIC算法性能，提出一种改进算法，在信源数目有误差的情况下该算法的性能良好。第五章针对多径干扰环境，在分析MMUSIC算法的基础上，本文提出了基于低秩矩阵逼近法的改进MUSIC算法(In this paper, firstly, the author illustrates the principles of smart antenna and adaptive beam forming, and then introduces some typical adaptive algorithms, the LMS ,CMA and RLS algorithms are analyzed and discussed and simulate them in the computer to prove their capability. but they have the disadvantage of high complexity, so they are not fit for practice. The paper analyses the conventional method rejecting spatial smoothing coherent interfering signals, which is spatial smoothing technique)
- 2009-07-02 22:43:06下载
- 积分：1
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work
说明： Matlab 模拟 CDMA 直接扩频。m序列生成矩阵为p(x) = 1 + x^5 + x^7 + x^8 + x^9 + x^13 + x^15。能画出每阶段的时域、频域图。(Matlab simulation of CDMA Direct Spread Spectrum. m sequence generated matrix for p (x) = 1+ x ^ 5+ x ^ 7+ x ^ 8+ x ^ 9+ x ^ 13+ x ^ 15. To draw each stage of the time domain, frequency domain Fig.)
- 2008-12-01 17:24:03下载
- 积分：1
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speechprotected1
speech recognition system matlab code
- 2011-05-08 02:42:34下载
- 积分：1
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114_image_processing_programs_by_MATLAB
114个数字图像处理MATLAB实验程序(114_image_processing_programs_by_MATLAB)
- 2010-07-27 15:20:58下载
- 积分：1
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HHT_EMD
一個把HHT程序用matlab實踐的檔
HHT Process(HHT Process)
- 2009-06-24 17:50:26下载
- 积分：1
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ALOHA
给出了一个关于多址接入协议ALoHA的ppt，和对应ppt中仿真图的源代码(this file folder includes a ppt about the mutiple access proctocal, and the related codes developed in Matlab for the figures in this ppt)
- 2013-11-10 11:20:39下载
- 积分：1
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Understanding-LTE-with-MATLAB
wiley 2014 新书 Understanding LTE with MATLAB，包含MATLAB 源代码以及相关协议解读，是从事LTE 研究人员的不可多得好书(wiley 2014 book Understanding LTE with MATLAB, MATLAB source code contains the interpretation and related agreements, is engaged in rare books LTE researchers)
- 2014-03-24 20:48:34下载
- 积分：1
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displayRelevantVisualWords
Optical flow or optic flow is the pattern of apparent motion of objects, surfaces, and edges in a visual scene caused by the relative motion between an observer (an eye or a camera) and the scene.[2][3] The concept of optical flow was first studied in the 1940s and ultimately published by American psychologist James J. Gibson[4] as part of his theory of affordance. Optical flow techniques such as motion detection, object segmentation, time-to-collision and focus of expansion calculations, motion compensated encoding, and stereo disparity measurement utilize this motion of the objects surfaces and edges.[5][6]
- 2012-03-31 23:44:49下载
- 积分：1
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dipum_toolbox_pcode
Image processing using Matlab additional material
- 2011-05-27 22:26:24下载
- 积分：1
