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[matlab例程0127444823

说明:Emission Tomography The fundamentals of PET and SPECT
<chrislu> 在 2025-06-25 上传 | 大小:14.8mb | 下载:0

[matlab例程1

说明:filter size image processing
<aaaaa> 在 2025-06-25 上传 | 大小:1kb | 下载:0

[matlab例程2

说明:filter line recognation iamge processing
<aaaaa> 在 2025-06-25 上传 | 大小:1kb | 下载:0

[matlab例程obstacle_detection

说明:obstacle avoidance,this document for obstacle avoidance for robot control
<ashil esmaeili> 在 2025-06-25 上传 | 大小:2.71mb | 下载:0

[数据结构常用算法juzhengsuanfa

说明:C++课程设计 矩阵算法 一种比较简单的方法 C语言初学者制作-C++ program design matrix algorithms a relatively simple way to produce C language for beginners
<王贵圆> 在 2025-06-25 上传 | 大小:329kb | 下载:0

[matlab例程ImageRotationCorrection_omidvarnia

说明:digital image processing broken_heart_repairing.m with matlabinclude 3 programs
<zeinab> 在 2025-06-25 上传 | 大小:39kb | 下载:0

[matlab例程asic3

说明:This pdf contains Hungarian notifications and asic methodologies .
<padma> 在 2025-06-25 上传 | 大小:202kb | 下载:0

[matlab例程Model1s

说明:it is pgm used in matlab
<babi> 在 2025-06-25 上传 | 大小:804kb | 下载:0

[matlab例程plot3d_2

说明:This function produces an image of a 3D object defined by matrix a(l,m,n) in terms of voxels the image is a view after rotating the object by angles alfa and beta (in degree) b is the image and d is its ditance to the viewer matrix The first figure d
<resident e> 在 2025-06-25 上传 | 大小:1kb | 下载:0

[matlab例程randgen2

说明:randgen(mu,mu1,mu2,cov1,cov2,cov3) = Random generation of Gaussian Samples in d-dimensions where d = 2 mu, mu1, mu2 = (x,y) coordinates(means) that the gaussian samples are centered around cov1, cov2, cov3 are the covariance matrices and will v
<resident e> 在 2025-06-25 上传 | 大小:1kb | 下载:0

[matlab例程fit_maxwell_pdf

说明: fit_maxwell_pdf - Non Linear Least Squares fit of the maxwellian distribution. given the samples of the histogram of the samples, finds the distribution parameter that fits the histogram samples. fits data to the probability of the form:
<resident e> 在 2025-06-25 上传 | 大小:2kb | 下载:0

[matlab例程fit_mix_2D_gaussian

说明:fit_mix_2D_gaussian - fit parameters for a 2D mixed-gaussian distribution using EM algorithm format: [u,covar,t,iter] = fit_mix_2D_gaussian( X,M ) input: X - input samples, Nx2 vector M - number of gaussians which are assumed to compose the
<resident e> 在 2025-06-25 上传 | 大小:2kb | 下载:0
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