MATLAB2010JC

说明：   exp-4: To observe the BER performance a SISO system with Non coherent modulation with Rayleigh fading channels.

分类器的实现，线性分类器的有关代码。matlap实现(Classifier to achieve a linear classifier on the code.)

matlab中编的基于遗传算法的转子故障特征选择的小程序，新手程度，仅供参考(matlab in the series based on genetic algorithm rotor fault feature selection of small programs, novice level, for reference only)

压缩感知，稀疏基为小波基，omp，典型的压缩感知代码(failed to translate)

几种自适应滤波器算法(several algorithm about adaptive signal processing)

sart ct reconstruction using sart. just for simulation. the file type is .7z

exercise1:为基于小波变化与局部能量的图像融合方法 exercise2:为基于自适应算法的图像融合算法 myfunction1~myfunction5:为性能指标评价函数(exercise1: To change and local energy based on wavelet image fusion method exercise2: adaptive algorithm based image fusion algorithm myfunction1 ~ myfunction5: performance indicators for the evaluation function)

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)

基于Heeb监督的单神经元自适应PID控制器S函数程序(Heeb supervision based on single neuron adaptive PID controller function S procedures)

DF加中继基于门限的中继选择，适合基础者学习。(DF plus relay threshold-based relay selection, suitable foundation to learn.)