color.m

说明：  DR定位卡尔曼滤波程序，用于巡逻机器人走直线时信号处理(DR positioning Kalman filtering procedures for patrol robot in a straight line, the signal processing)

信号与系统基础知识包括连续信号与模型、离散信号与模型；常用信号变换包括Z变换、Chirp Z变换、FFT变换、DCT变换和Hilbert变换等；离散系统结构包括IIR、FIR和Lattice结构；IIR滤波器设计包括模拟和数字低通、高通、带通与带阻滤波器设计，以及基于冲激响应不变法和双线性Z变换法的IlR滤波器设计等；FIR滤波器设计包括基于窗函数、频率抽样法和切比雪大逼近法的FIR滤波器设计；平稳信号分析包括经典功率谱估计、基于参数模型的功率谱估计和基于非参数模型的功率谱估计；非平稳信号分析包括STFT变换、Gabor展开、Wigner-Ville分布与Choi-Williams分布；非高斯信号分析包括基于非参数法的双谱估计、基于参数模型的双谱估计，以及双谱估计的应用；信号处理的GUI实现包括滤波器设计与分析的FDATool工具和滤波器设计与信号分析的SPTool工具。(signals and systems based on knowledge, including continuous signal with the model, discrete signal and model; Common signals include transform Z transform, chirp Z-transform, FFT transform. DCT and Hilbert transform; Discrete system architecture including IIR, FIR and Lattice structure; IIR filter design, including analog and digital low-pass, high-pass, band-pass and band stop filter design, Based on the impulse response of the same law and bilinear Z transform the IlR filter design; FIR filter design including on the basis of the window function, frequency sampling and snow all over the big approximation of FIR filter design; stationary signal analysis include classical power spectrum estimation, Based on the model parameters of the power spectrum estimation and non- parametric model b)

说明：  EDA经典算法PBIL程序，与大家分，共同进步(PBIL algorithm EDA classical procedures, and that we can progress together)

DBPSK transreceiver design model using simulink

说明：  image processing-no of intensity levels

计算SENSE重建图像中的g-factor,这是并行磁共振成像SENSE算法的关键一步(G-factor is the metric to quantify the amplificaiton of noise power in reconstructing SENSE accelerated image. The detail was presented in Pruessmann s 1999 Magn. Reson. Med. paper. In theory, g-factor is the pixel-by-pixel ratio of the image variance between the SENSE reconstructed image and un-accelerated image. And g-factor depends on: (1) the k-space data trajectory (2) coil sensitivit profiles (3) noise covariance matrix of the array coil)

matlab中的ls-svm工具包，是最小二乘支持向量机算法，可用于解决非线性的回归问题。(ls-svm tool in the Matlab package, least squares support vector machine algorithm can be used to solve nonlinear regression problems.)

this source code is very good

一个KLMAN滤波的matlab程序,仿真了车辆行驶的跟踪过程(A KLMAN filter matlab program, the simulation process of tracking a moving vehicle)

Matlab GUI编程中文参考手册，以及一些基本的程序介绍(Matlab GUI Programming Reference Manual, as well as some basic procedures for introduced)