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256x256
256x256 Benchmarks for Image Processing
- 2010-02-22 18:26:41下载
- 积分:1
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Newton-rapahson
牛顿拉夫森法用来解决极大似然估计的问题。很好用。(Newton La Fusen method to solve the problem of maximum likelihood estimation. Good use.)
- 2011-05-25 15:24:12下载
- 积分:1
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digital_signal_processing_usrp
此压缩包是关于USRP中的数字信号处理,包括锁相环、数字滤波器和数据类型转换(digital filer、data convertion)
- 2011-12-16 22:15:00下载
- 积分:1
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fisheyeCorr
可实现鱼眼校正功能,主要包括有效区域的提取与鱼眼校正(The function of ROI extract and fisheye correction is written by matlab)
- 2018-10-08 14:56:40下载
- 积分:1
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zuixiaoercheng
这是系统辨识的典型例题及其MATLAB仿真程序(This is a typical example of system identification and simulation program MATLAB)
- 2009-05-16 20:27:46下载
- 积分:1
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adaptive-filter-of-MATLAB
matlab 的自适应滤波器仿真程序,包括LMS算法的仿真程序,NLMS算法的仿真程序(adaptive filter matlab simulation program, including the LMS algorithm of the simulation program, NLMS algorithm simulation program)
- 2011-09-10 22:21:46下载
- 积分:1
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OOP
object-oriented programming
- 2013-11-25 22:36:53下载
- 积分:1
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Inertial-algorithm-
完整的惯性领域解算数学模型及解算算法,可以进行理论仿真及实验数据验证。(Complete inertial field solver solver algorithms and mathematical models can be theoretical simulation and experimental data validation.)
- 2013-12-21 13:04:16下载
- 积分:1
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time_delay
用多个正弦产生仿真信号,两个阵元接受到信号后,估计两信号的延迟(Simulation generated by a number of sinusoidal signals, the two array element received signal, it is estimated that the two signals delayed)
- 2008-01-14 21:27:15下载
- 积分:1
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RVM_matlabToolBox
相关向量机(RVM)的matlab源程序,包含快速算法,内含代码使用说明。 RVM采取是与支持向量机相同的函数形式稀疏概率模型,对未知函数进行预测或分类。 优点: (1) 不仅仅输出预测目标量的点估计值,还可以输出预测值的分布. (2) 使用更少数量的支持向量,从而显著减少输出目标量预测值的计算时间. (3) RVM不需要估计过多的参数. (4) RVM对是否满足Mercer 定理的核函数没有限制,适应性更好(Relevance Vector Machine (RVM) of the matlab source code, including fast algorithm that contains code for use. RVM support vector machine is taken the same functional form sparse probabilistic model to predict the unknown function or classification. Advantages: (1) is not only the amount of output predicted target point estimates, but also the distribution of predicted values can be output. (2) using a smaller number of support vectors, thereby significantly reducing the output target amount predicted value calculation time. (3) RVM does not require excessive parameter estimation. (4) RVM meets Mercer theorem on the kernel function is not limited, and better adaptability)
- 2013-11-21 11:05:48下载
- 积分:1