calculate_farfield

alpha trimmed mean filter for image

考虑一长度为D，宽度为L的理想均匀面阵天线，并用Matlab画出其二维波束方向图。(Consider an ideal uniform planar array antenna with length D and width L, and draw its two-dimensional beam pattern with MATLAB.)

说明：  该例程实现了男女声音识别的算法，识别准确率较高(This routine realizes the algorithm of male and female voice recognition, and the recognition accuracy is high.)

Library to handle and visualize geometric primitives such as points,lines, circles and ellipses, polygons... The goal is to provide a low-level library for manipulating geometrical primitives, making easier the development of more complex geometric algorithms.

edge detection using fuzzy and canny operator

基于MATLAB/simulink仿真平台的循环流化床锅炉燃烧系统的密相区仿真模型(Based on MATLAB/simulink simulation platform circulating fluidized bed boiler combustion system simulation model of dense phase region)

RNNSIM v.2 package contains a number of m-files for training and evaluation of the random neural network. All functions have been thoroughly tested. After downloading the separate files or the zipped file, make sure that they are stored or extracted in the directory /rnnsimv2 Below an overview of the files contained in this directory along with a brief description of what they do. The on-line help facility explains how to call the different functions. You simply write help <function-name> in the MATLAB command window. Along with the m-files in this directory you will find a manual for the simulator in PDF format (rnnsimv2.pdf). Start by printing this out and read the release notes. Two simple demonstration programs are given to illustrate how most of the functions work.

DC Motor control model

FDTD中对仿真图像模拟显示，方便对于时间域有限差分的相关模拟就行研究(FDTD simulation image simulation to facilitate research on the finite difference time domain simulation)

计算赫斯特指数Calculates the generalized Hurst exponent H(q) of a stochastic variable x(t) (a time series) the scaling of the renormalized q-moments of the distribution <|x(t+r)-x(t)|^q>/<x(t)^q> ~ r^[qH(q)] The value of H(q) give indication about the fractal nature of the signal. H(q) = 0.5 corresponds to a Brownian motion, deviations form 0.5 and dependency on q are indications of multi-fractality and time-correlations.(Calculates the generalized Hurst exponent H(q) of a stochastic variable x(t) (a time series) the scaling of the renormalized q-moments of the distribution <|x(t+r)-x(t)|^q>/<x(t)^q> ~ r^[qH(q)] The value of H(q) give indication about the fractal nature of the signal. H(q) = 0.5 corresponds to a Brownian motion, deviations form 0.5 and dependency on q are indications of multi-fractality and time-correlations.)