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duandianjiance
语音信号端点检测仿真，内容涉及短时能量及过零率的计算，自相关函数的的计算。(voice endpoint detection signal simulation, which relates to short-term energy and zero rate calculation, the autocorrelation function of the calculation.)
- 2006-06-09 00:32:03下载
- 积分：1
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uongluong1
it is very imoportant file
- 2010-05-13 01:26:39下载
- 积分：1
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fdtd1D_Susan
美国威斯康辛麦迪逊大学苏珊教授编写的一维时域有限差分法算法(1D Finite Domain Time Domain algorithm from Professor Susan)
- 2013-11-29 10:48:15下载
- 积分：1
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BrooknKalman.pdf
Book algorithm about kalman filter
- 2014-12-19 17:57:38下载
- 积分：1
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BP-AND-PID
卫星姿态控制的matlab/simulink BP神经网络PID控制器设计源代码及模型资料等(matlab/simulink BP PID)
- 2020-10-01 17:07:44下载
- 积分：1
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BCFCM version
说明： Bias-corrected fuzzy c-means (BCFCM) clustering compensates for two sources of uncertainty by modeling noise and bias fields
- 2019-07-05 02:49:25下载
- 积分：1
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control
自动控制原理中应用仿真软件对控制系统的时域分析的研究和比较(The application of the principle of automatic control of the control system simulation software, the time-domain analysis and comparison of)
- 2009-04-28 19:42:25下载
- 积分：1
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linearandintegercode
线性规划问题(单纯形法、完整单纯形法与修正单纯形法)与整数规划问题(割平面法、分支定界法与0-1规划)的matlab源程序(matlab source programs of linear programming including simple method, complete simple method and modified simple method and integer programming including dividing plane method, branch and bound method and 0-1 programming method.)
- 2010-01-23 17:22:04下载
- 积分：1
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xiaobosanjiefenjiechonggou
说明： 对心音信号进行小波三阶分解重构（默认阈值，软阈值）的matlab程序(wavelet decompose and redistribute matlab)
- 2011-04-05 15:55:53下载
- 积分：1
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adaboost_version1e
这是一个经典的形变模型实施,在一个单一的文件用简单的可以理解的代码。
功能包括两部分一个简单的弱分类器和一个促进部分:
弱分类器试图找到最佳阈值的数据维数对数据进行分离成两个阶级1和1
要求的进一步提高分类器部分迭代,每一步是变化分类权重miss-classified例子。这造成了一连串的“弱分类器”,表现得像一个“强大分类器”
(This a classic AdaBoost implementation, in one single file with easy understandable code.
The function consist of two parts a simple weak classifier and a boosting part:
The weak classifier tries to find the best threshold in one of the data dimensions to separate the data into two classes-1 and 1
The boosting part calls the classifier iteratively, after every classification step it changes the weights of miss-classified examples. This creates a cascade of "weak classifiers" which behaves like a "strong classifier"
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)
- 2012-04-23 13:17:57下载
- 积分：1
