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CDMA-technical-training-material
CDMA技术培训资料，希望对学习CDMA的同学有帮助！(CDMA technical training material)
- 2010-10-12 10:08:21下载
- 积分：1
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EKF-SLAM-Simulator
说明： 本程序包设计了一个利用Matlab编写的基于EKF的SLAM仿真器，可用于机器人的路径规划的仿真实验设计。(This package designed a written Matlab, the SLAM EKF-based simulator can be used for robot path planning simulation design.)
- 2011-03-06 15:12:05下载
- 积分：1
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knnl
classification reseau de neurone
- 2012-03-27 11:11:05下载
- 积分：1
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SIMO_simulation
single input multiple output matlab simulation..
- 2014-09-02 19:06:30下载
- 积分：1
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kmeans
基于K-means的模糊聚类分析方法，很有用的(Based on the fuzzy K-means cluster analysis, very useful)
- 2010-12-11 10:02:37下载
- 积分：1
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drives
drive design for induction machine
- 2013-05-22 21:16:00下载
- 积分：1
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Ultra-wideband-Positioning-Systems
超宽带定位系统，较好的一本书，涉及很多方面的内容(Ultra-wideband positioning system, a good book, involving many aspects)
- 2014-01-10 03:11:52下载
- 积分：1
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metal_reflection_meep
在MIT的meep中，用来计算银表面的折射率和吸收率。用于FDTD算法。(Meep at MIT, the silver surface used to calculate the refractive index and absorption rate. For the FDTD algorithm.)
- 2013-07-26 22:11:07下载
- 积分：1
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Using-Over-complete-subband-
Using Over complete subband
- 2014-02-20 08:44:32下载
- 积分：1
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2dgaussian
汽车高斯曲面拟合
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2程序，以适应到表面二维高斯：
子= A *的进出口（ -（（西为X0）^2/2/sigmax^2 +（艺Y0的）^2/2/sigmay^ 2）。。）+ b的
这些例程是自动在某种意义上说，他们并不需要出发对模型参数的猜测规范。
autoGaussianSurfML（十一，彝，子）适合通过对模型参数的最大似然（最小二乘）。它首先计算了该模型在许多可能的参数值，然后选择最佳质量设置和细化与lsqcurvefit它。
autoGaussianSurfGS（十一，彝，紫）的估计，通过指定数据的贝叶斯生成模型，然后采取通过从模型吉布斯抽样样本后ofthis模型参数。这种(Auto Gaussian Surface fit
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2 routines to fit a 2D Gaussian to a surface:
zi = a*exp(-((xi-x0).^2/2/sigmax^2+ (yi-y0).^2/2/sigmay^2))+ b
The routines are automatic in the sense that they do not require the specification of starting guesses for the model parameters.
autoGaussianSurfML(xi,yi,zi) fits the model parameters through maximum likelihood(least-squares). It first evaluates the quality of the model at many possible values of the parameters then chooses the best set and refines it with lsqcurvefit.
autoGaussianSurfGS(xi,yi,zi) estimates the model parameters by specifying a Bayesian generative model for the data, then taking samples from the posterior ofthis model through Gibbs sampling. This method is insensitive to local minimain posterior and gives meaningful error bars (Bayesian confidence intervals))
- 2011-05-23 10:36:52下载
- 积分：1
