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fcm
基于matlab的fcm（模糊C）图像分割代码，适于matlab和图像分割入门学习(failed to translate)
- 2013-05-08 09:24:06下载
- 积分：1
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first-order-difference-
matlab数据处理程序：用一阶差分法剔除数据(Excluding first-order difference data)
- 2021-04-19 19:48:51下载
- 积分：1
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conjgrad123
To solve Ax=b - input A, b, x0 (initial guess), ni (number of iteration) - output
- 2010-11-05 23:23:06下载
- 积分：1
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Thecat-and-mouse--Simulink
用simulink对经典的猫捉老鼠的一个仿真，简单而且容易理解(Classic cat and mouse on a simulation)
- 2011-04-25 12:50:38下载
- 积分：1
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testfiresim
Test fire simulation
- 2011-05-26 06:32:10下载
- 积分：1
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hopfield-NET
菲尔德网络知识，对神经网络只是大大的补充，该算法应用很广。(Rumsfeld network knowledge, the neural network is greatly supplement, the algorithm is widely used.)
- 2013-11-01 16:41:41下载
- 积分：1
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ipad_iphone_sensorgroup
使用MATLAB从你的iPhone或iPad上的内置传感器采集传感器数据(Use MATLAB to acquire sensor data from built-in sensors on your iPhone or iPad.
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- 2013-11-18 14:36:32下载
- 积分：1
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jilei
matlab实现信号的相参积累和非相参积累源代码(matlab realization the signal coherent integration and non-coherent accumulation of source code)
- 2020-11-06 19:39:49下载
- 积分：1
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linear_system_identification.tar
The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order (The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order)
- 2008-08-03 10:18:16下载
- 积分：1
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FrequencyFilt
m.file frequency filter for image processing applications
- 2011-01-24 17:42:08下载
- 积分：1
