MonteCarlo

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 vary changing the shape of the distribution, example: cov = sigma^2*Identity Matrix, where sigma^2 = a scalar N = the number of gaussian samples used are provided as user input, A test set of N/2 and a training set of N/2 gaussian samples is also generated Output is directed to the command window and a plot of the distributions are generated

GOOD PLATFORM TO LEARN THE CODES OF TRACKING ON THE OBJECT OF BODY FALLING ON THE GROUND

General Embedded Quantization for Wavelet-Based Lossy Image Coding

Image segmentation plays an important role in computer vision and image processing applications. The motivation of this project is Image Segmentation with the presence of Intensity inhomogeneities. Intensity inhomogeneity often occurs in real world images due to spatial variations in illumination and imperfections of imaging devices

This exchange file creates a clickable image map for a figure with links to multiple data sources

Example of a digital data transmission implementing GMSK modulation This Simulink model simulates as an example the transmission and reception of random digital data modulated with GMSK. The purpose of this model is to illustrate how part of the GSM transmission and reception works. It also measures the BER, affected by an AWGN channel (Example of a digital data transmission The need lementing GMSK modulation This Simulink model simulates as an example the transmission and re Arjen of random digital data modulated with G. MSK. The purpose of this model is to illustrate h ow part of the GSM transmission and reception wo rks. It also measures the BER. affected by an AWGN channel)

hht希尔伯特黄变化的matlab实现不错试过了(hht Hilbert Huang changing tried matlab realize good)

finite element method use machanical engineer to solve the problem about finite

Source code for Radial basic function for classification

3 Dimension simultaneous localization and mapping (SLAM) problem asks if it is possible for a mobile robot to be placed at an unknown location in an unknown environment and for the robot to incrementally build a consistent map of this environment while simultaneously determining its location within this map