非线性动力学 nonlinear

说明：  自己写的一个计算空间时频分布的程序，可知指定Cohen类分布类型WVD，CWD，PWVD，SPWVD，BJD(himself in a room when calculating the frequency distribution procedures, we can see Cohen category designated distribution type WVD, CWD, Wigner, SPWVD, BJD etc.)

讨论匹配滤波器对不同形式的PAM信号进行接收的情况。并研究在高斯白噪声环境中传输的改善程度(Discussion of the matched filter for different forms of PAM signal reception conditions. And to study the white Gaussian noise environment in the improvement of transmission)

source code for finding lung extraction

说明：  material property for RCWA calculation

nonlinear system identification using neural networks on matlab

ksvd字典学习算法和改进的ksvd字典学习算法，并自动计算psnr。(ksvd dictionary learning algorithm and improved ksvd dictionary learning algorithm and automatically calculates psnr.)

slm matlab 仿真代码 各种完备M文件(slm matlab simulation code of a complete M-file)

In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar -xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets. (In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar-xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets. )

Convert a color image between color representations. B = COLORSPACE(S,A) converts the color representation of image A where S is a string specifying the conversion. S tells the source and destination color spaces, S = dest<-src , or alternatively, S = src->dest . Supported color spaces are RGB R G B Red Green Blue (ITU-R BT.709 gamma-corrected) YPbPr Luma (ITU-R BT.601) + Chroma YCbCr / YCC Luma + Chroma ("digitized" version of Y PbPr) YUV NTSC PAL Y UV Luma + Chroma YIQ NTSC Y IQ Luma + Chroma YDbDr SECAM Y DbDr Luma + Chroma JPEGYCbCr JPEG-Y CbCr Luma + Chroma HSV / HSB Hue Saturation Value/Brightness HSL / HLS / HSI Hue Saturation Luminance/Intensity XYZ CIE XYZ Lab CIE L*a*b* (CIELAB) Luv CIE L*u*v* (CIELUV) Lch CIE L*ch (CIELCH)(Convert a color image between color representations. B = COLORSPACE (S, A) converts the color representation of image A where S is a string specifying the conversion. S tells the source and destination color spaces, S = ' dest <-src' , or alternatively, S = ' src-> dest' . Supported color spaces are ' RGB' R' G' B ' Red Green Blue (ITU-R BT.709 gamma-corrected)' YPbPr ' Luma (ITU-R BT.601 )+ Chroma ' YCbCr' /' YCC' Luma+ Chroma ( " digitized" version of Y' PbPr) ' YUV' NTSC PAL Y' UV Luma+ Chroma ' YIQ' NTSC Y' IQ Luma+ Chroma ' YDbDr' SECAM Y ' DbDr Luma+ Chroma ' JPEGYCbCr' JPEG-Y' CbCr Luma+ Chroma ' HSV' /' HSB' Hue Saturation Value/Brightness' HSL ' /' HLS ' /' HSI ' Hue Saturation Luminance/Intensity' XYZ ' CIE XYZ' Lab ' CIE L* a* b* (CIELAB)' Luv ' CIE L* u* v* (CIELUV)' Lch ' CIE L* ch (CIE)

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