vehicle-sub-system

Matlab code for demodulating QPSK signal

本代码为计算快速汉克变换的matlab源程序。快速汉克变换为经典的数值算法，在地球物理建模中有极其重要的地位(This code for calculations quickly Hank transform matlab source. Rapid Hank transformation as a classic numerical algorithm in geophysics modeling in a very important position)

基于matlab的非线性动力学liu混沌系统的分岔图(the plotbasedon Nonlinear Dynamics Liu chaotic system bifurcation diagram)

学习matlab的同学赶紧下啊，非常有用的。 特别是学编程的同学。(very cool optimal course for all.)

MATLAB空时分组码仿真，用于检测编码性能(MATLAB simulation of space-time block codes for the detection of coding performance)

principal component analysis

ICA盲源分离方法，可以很快的分离混合信号，对初学者有很大的帮助。(ICA blind source separation methods, can quickly separate mixed signal, there is a great help for beginners.)

BPSK的simulink仿真，及其完整的参数设置，频谱分析图和星座图(Simulink simulation of BPSK, and a complete set of parameters, the spectrum and constellation diagram analysis)

说明：  该算法实现了宽带麦克风阵列的波束形成，主要采用了频域DFT和时域FIR波束形成器(The algorithm for broadband microphone array beam-forming, the main frequency domain using DFT and time-domain FIR Beamformer)

A general technique for the recovery of signicant image features is presented. The technique is based on the mean shift algorithm, a simple nonparametric pro- cedure for estimating density gradients. Drawbacks of the current methods (including robust clustering) are avoided. Feature space of any nature can be processed, and as an example, color image segmentation is dis- cussed. The segmentation is completely autonomous, only its class is chosen by the user. Thus, the same program can produce a high quality edge image, or pro- vide, by extracting all the signicant colors, a prepro- cessor for content-based query systems. A 512  512 color image is analyzed in less than 10 seconds on a standard workstation. Gray level images are handled as color images having only the lightness coordinate(A general technique for the recovery of sig ni cannot image features is presented. The techni que is based on the mean shift algorithm, a simple nonparametric pro-cedure for estimat ing density gradients. Drawbacks of the curren t methods (including robust clustering) are av oided. Feature space of any nature can be proces sed, and as an example, color image segmentation is dis-cussed. The se gmentation is completely autonomous. only its class is chosen by the user. Thus, the same program can produce a high quality edge image, or pro-vide. by extracting all the signi cannot colors, a prepro- cessor for content-based query syste ms. A 512,512 color image is analyzed in less than 10 seconds on a standard workstation. Gray 4ISR l images are handled as color images having only the lightness c)