SDFT解调与普通DFT解调算法的对比

薛定宇教授 ctrllab工具箱3.0；PID参数仿真用。 使用方法：1）解压，并在matlab下导入路径；2）在命令窗口执行ctrllab即可。 (Professor Xue Dingyu ctrllab Toolbox 3.0 PID parameters in simulation. Usage: 1) extract and import under the matlab path 2) In the command window to execute ctrllab.)

基于蒙特卡罗法的2FSK系统抗噪声性能仿真(The matlab Monte Carlo the law 2FSK system anti-noise performance simulation)

多用户MIMO预编码技术的对比，bd预编码，zf预编码，mmse预编码等，对学习多用户mimo系统很有帮助。(Multi-user MIMO precoding technology comparison, bd precoding, zf precoding, mmse precoding, etc., to learn multi-user mimo system is very helpful.)

image contrast enhancement

LZ compression LZ decompression

基于遗传算法的神经网络例子，运行结果相当理想，每一步都是源代码，宝贵。(Examples of genetic algorithms based on neural networks, operating result is quite satisfactory, every step is the source code, valuable.)

a design methodology is introduced that blends the classical PID and the fuzzy controllers in an intelligent way and thus a new intelligent hybrid controller has been achieved. Basically, in this design methodology, the classical PID and fuzzy controller have been combined by a blending mechanism that depends on a certain function of actuating error. Moreover, an intelligent switching scheme is induced on the blending mechanism that makes a decision upon the priority of the two controller parts namely, the classical PID and the fuzzy constituents. The simulations done on various processes using the new hybrid fuzzy PID controller provides ‘better’ system responses in terms of transient and steady-state performances when compared to the pure classical PID or the pure fuzzy controller applications. The controller parameters are all tuned by the aid of genetic search algorithm.

对控制装置及仪表的控制系统进行仿真，并给出性能分析(Control devices and instrumentation control system simulation and performance analysis is given )

qpsk 和 qam的完整仿真，非常详细(qpsk qam and the integrity simulation, very detailed)

学习压缩感知时自己编写的初步重建程序，有利于加深理解压缩感知的理论(Preliminary reconstruction program, write your own learning compressed sensing, a better understanding of the theory of compressed sensing)