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matlab-difference-in-fplot-and-Plot
matlab中fplot与Plot的区别，希望对大家有所帮助。(matlab difference in fplot and Plot, we want to help.)
- 2011-01-20 10:40:43下载
- 积分：1
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Sigmon-K.-MATLAB-Primer-(3rd-ed.-1993)(en)(34s)
The purp ose of this Primer is to help you b egin to use MATLAB. It is not intendedto b e a substitute for the User s Guide and Reference The purpose of this Primer is to help you begin to use Matlab.The Primer can best be used hands-on. You are encouraged to work at the computer as you read thePrimer and freely exp eriment with examples. This Primer, along with the on-line helpfacility, usually suce for students in a class requiring use of MATLAB
- 2011-12-03 04:32:04下载
- 积分：1
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matlab2
matlab高级编程 课本中的源代码 作者谷源涛(" Matlab Advanced Programming," in the source code for textbook authors Gu Yuan Tao)
- 2009-11-10 23:38:44下载
- 积分：1
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cordic_midterm_report[1]
一篇基于Matlab到OFDM研究开发的论文，有需要的朋友可以下载看看(An OFDM-based research and development of Matlab to the papers, a friend in need can be downloaded to see)
- 2010-11-21 00:15:20下载
- 积分：1
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digital-optical-coherent-detection
说明： 偏振复用差分相移键控信号的数字相干解调与偏振解复用算法研究
(Digital Optical Coherent Detection of Polarization-Multiplexed
Differential Phase Shift Keying Signal and Analysis of
Adaptive Digital Polarization Demultiplexin
)
- 2011-04-08 12:48:53下载
- 积分：1
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tuxiangxiangpeizhun
这里是图像配准的程序，木前就到那么多，希望对你们有帮助。(Here is the image registration procedures, wood before you to so much, and I hope to help you.
)
- 2012-11-21 22:40:10下载
- 积分：1
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CS_UKF
说明： CS_UKF当前统计模型无迹卡尔曼滤波跟踪算法CS_UKF当前统计模型无迹卡尔曼滤波跟踪算法(CS_UKF)
- 2010-04-30 17:27:26下载
- 积分：1
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RLS_Algorithms
recursive least square (RLS) algorithm using matlab with examples
- 2013-12-21 16:17:52下载
- 积分：1
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LPC
语音信号处理中基音周期的提取算法，用线性预测的基本算法原理，matlab实现。(Speech signal processing in pitch extraction algorithm, the basic algorithm with linear prediction theory, matlab implementation.)
- 2009-12-14 20:14:30下载
- 积分：1
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MyKmeans
实现聚类K均值算法： K均值算法：给定类的个数K，将n个对象分到K个类中去，使得类内对象之间的相似性最大，而类之间的相似性最小。 缺点：产生类的大小相差不会很大，对于脏数据很敏感。 改进的算法：k—medoids 方法。这儿选取一个对象叫做mediod来代替上面的中心 的作用，这样的一个medoid就标识了这个类。步骤： 1，任意选取K个对象作为medoids（O1,O2,…Oi…Ok）。 以下是循环的： 2，将余下的对象分到各个类中去（根据与medoid最相近的原则）； 3，对于每个类（Oi）中，顺序选取一个Or，计算用Or代替Oi后的消耗—E（Or）。选择E最小的那个Or来代替Oi。这样K个medoids就改变了，下面就再转到2。 4，这样循环直到K个medoids固定下来。 这种算法对于脏数据和异常数据不敏感，但计算量显然要比K均值要大，一般只适合小数据量。(achieving K-mean clustering algorithms : K-means algorithm : given the number of Class K, n will be assigned to target K to 000 category, making target category of the similarity between the largest category of the similarity between the smallest. Disadvantages : class size have no great difference for dirty data is very sensitive. Improved algorithms : k-medoids methods. Here a selection of objects called mediod to replace the center of the above, the logo on a medoid this category. Steps : 1, arbitrary selection of objects as K medoids (O1, O2, Ok ... ... Oi). Following is a cycle : 2, the remaining targets assigned to each category (in accordance with the closest medoid principle); 3, for each category (Oi), the order of selection of a Or, calculated Oi Or replace the consumption-E (Or))
- 2005-07-26 01:32:58下载
- 积分：1
