Description: ICP fit points in data to the points in model. Fit with respect to minimize the sum of square errors with the closest model points and data points.
Ordinary usage:
[R, T] = icp(model,data)
INPUT:
model - matrix with model points,
data - matrix with data points,
OUTPUT:
R - rotation matrix and
T - translation vector accordingly
so
newdata = R*data + T .
newdata are transformed data points to fit model
see help icp for more information
-ICP fit points in data to the points in model. Fit with respect to minimize the sum of square errors with the closest model points and data points.
Ordinary usage:
[R, T] = icp(model,data)
INPUT:
model- matrix with model points,
data- matrix with data points,
OUTPUT:
R- rotation matrix and
T- translation vector accordingly
so
newdata = R*data+ T .
newdata are transformed data points to fit model
see help icp for more information
Platform: |
Size: 5120 |
Author:阳关 |
Hits:
Description: Type Classification Code:
main.m (program control)
discretize.m (converts image to discrete values)
plotimg.m (plots images)
dirImg.m (computes the directional image)
extract.m (extracts square portion of image - called by dirImg)
slitSum.m (computes the slit sum direction - called by dirImg)
tileImg.m (tiles the image and computes new directions)
averImg.m (smoothes the image)
angleImg.m (computes the angles from the vector representation)
Poincare.m (computes the core-delta points)
temp.m (extracts the core-delta points and locations)
Correlation Code:
proj.m (program control)
plotimg.m (plots images)
discretize.m (converts image to discrete values)
normalize.m (normalizes images)
corrfft.m (computes the correlation)
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-Type Classification Code: main.m (program control) discretize.m (converts image to discrete values) plotimg.m (plots images) dirImg.m (computes the directional image) extract.m (extracts square portion of image- called by dirImg ) slitSum.m (computes the slit sum direction- called by dirImg) tileImg.m (tiles the image and computes new directions) averImg.m (smoothes the image) angleImg.m (computes the angles from the vector representation) Poincare.m (computes the core-delta points) temp.m (extracts the core-delta points and locations) Correlation Code: proj.m (program control) plotimg.m (plots images) discretize.m (converts image to discrete values) normalize. m (normalizes images) corrfft.m (computes the correlation )-------------------------------------------------------------------------------- Platform: |
Size: 6144 |
Author:小熊 |
Hits:
Description: 本文介绍了基于MATLAB软件在《信号与系统》课程教学中的仿真实验,通过抽样信号的表征、周期方波信号的傅立叶级数分解与合成、余弦信号的相加与相乘、RLC带通滤波器的频率特性等仿真实验,说明了将MATLAB应用于教学实践中的重要作用和意义。-This article describes the MATLAB-based software in the " Signals and Systems" course teaching simulation, by sampling the signal characterization, cycle square wave signal of the Fourier series decomposition and synthesis, and the sum of cosine signal is multiplied, RLC bandpass filter the frequency characteristics simulation, MATLAB used to illustrate the important role of teaching practice and significance. Platform: |
Size: 210944 |
Author:fenghaixiang |
Hits:
Description: 包括kf，ekf，pf，upf可以自己定制模型参数，完成滤波-ReBEL currently contains most of the following functional units which can be used for state-, parameter- and joint-estimation:
Kalman filter
Extended Kalman filter
Sigma-Point Kalman filters (SPKF)
Unscented Kalman filter (UKF)
Central difference Kalman filter (CDKF)
Square-root SPKFs
Gaussian mixture SPKFs
Iterated SPKF
SPKF smoothers
Particle filters
Generic SIR particle filter
Gaussian sum particle filter
Sigma-point particle filter
Gaussian mixture sigma-point particle filter
Rao-Blackwellized particle filters
The italicized algorithms above are not fully functional yet (or included in the current release), but will be in the next or future releases. The code is designed to be as general, modular and extensible as possible, while at the same time trying to be as computationally efficient as possible. It has been tested with Matlab 7.2 (R2006a).
Platform: |
Size: 1608704 |
Author:zhangsimin |
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Description: MATLAB提供了各种曲线拟合方法，例如：Exponential, Fourier, Gaussing, Interpolant, Polynomial, Power, Rational, Smoothing Spline, Sum of Functions, Weibull等，当然，也可以使用 Custom Equations.
cftool不仅可以绘制拟合后的曲线、给出拟合参数，还能给出拟合好坏的评价参数(Goodness of fit)如SSE, R-square, RMSE等数据，非常好用。但是如果我们已经确定了拟合的方法，只需要对数据进行计算，那么这种GUI的操作方式就不太适合了，比如在m文件中就不方便直接调用cftool。
-matlab has given a lot of method for curve combine ,we will give a new method and provide a matlab code. Platform: |
Size: 50176 |
Author:李平 |
Hits:
Description: 计算了0.001-0.999之间数字的平方和，并给出图形，并与matlab自身的函数power进行了比较，给出了差值的图形-Calculates the square sum of the Numbers between 0.001 0.999, and the graphics is given, and with the function of matlab power are compared, and the difference of the graphics is presented Platform: |
Size: 15360 |
Author:shujian |
Hits:
Description: K-means算法是硬聚类算法，是典型的基于原型的目标函数聚类方法的代表，它是数据点到原型的某种距离作为优化的目标函数，利用函数求极值的方法得到迭代运算的调整规则。K-means算法以欧式距离作为相似度测度，它是求对应某一初始聚类中心向量V最优分类，使得评价指标J最小。算法采用误差平方和准则函数作为聚类准则函数。(The K-means algorithm is a hard clustering algorithm, which is representative of the prototype based objective function clustering method. It is the distance from the data point to the prototype as the objective function of the optimization, and the method of using the function to find the extremum is used to get the adjustment rules of the iterative operation. The K-means algorithm takes Euclidean distance as the similarity measure, it is to find the V optimal classification corresponding to an initial cluster center vector, so that the evaluation index J is the smallest. The error square sum criterion function is used as a clustering criterion function.) Platform: |
Size: 1024 |
Author:Daizy7 |
Hits:
Search - sum of square matlab