LCMV优化设计阵列处理信号matlab源程序

Its a useful book for aptitude and also technical aptitude.

本文详细介绍了运用matlab 进行车牌定位分割的算法原理和算法实现，有兴趣的可以(This paper introduces in detail the use of matlab for license plate location algorithm and segmentation algorithm, interested can)

matlab code for BPSK generation without using inbuilt functions and in AWGN channel

cordic,matlab,sin,cos,atan,sqrt

复杂网络求取最短路径长度，可注明孤点和独立的点集(Complex network to strike a path length can be specified independent solitary point and point set)

说明：  所谓下垂控制就是选择与传统发电机相似的频率一次下垂特性曲线（Droop Character）作为微源的控制方式，即分别通过P/f下垂控制和Q/V下垂控制来获取稳定的频率和电压，这种控制方法对微网中的微源输出的有功功率和无功功率分别进行控制，无需机组间的通信协调，实现了微源即插即用和对等控制的目标，保证了孤岛下微电网内电力平衡和频率的统一，具有简单可靠的特点(The so-called droop control is to select the Droop Character, which is similar to the traditional generator, as the control mode of micro-source. That is to say, the stable frequency and voltage are obtained by P/f droop control and Q/V droop control respectively. This control method controls the active power and reactive power of micro-source output in the micro-grid separately, without the need of communication coordination between the units. It realizes the goal of micro-source plug-and-play and peer-to-peer control, guarantees the unification of power balance and frequency in micro-grid under islands, and has the characteristics of simplicity and reliability.)

说明：  常用的matlab算法源码，包括统计分析、图形图像等(some matlab source code programs about statastic analysis and figure processing.)

说明：  高斯白噪声无线通信信道下的误码率仿真，希望对你的学习有用(Gaussian white noise of wireless communication channel under BER simulation, you would like to learn useful)

用于信道均衡的RLS算法，可用于水声信道的改进算法(RLS algorithm for channel equalization, the improved algorithm can be used for underwater acoustic channel)

This is code for Haralick feature extraction for image in matlab. The basis for these features is the gray-level co-occurrence matrix. This matrix is square with dimension Ng, where Ng is the number of gray levels in the image. Element [i,j] of the matrix is generated by counting the number of times a pixel with value i is adjacent to a pixel with value j and then dividing the entire matrix by the total number of such comparisons made.