m_seqU

利用MATLAB对语音进行端点检测，检测起始端和终点段(Using MATLAB speech endpoint detection, detecting the start and end segment ends)

一种用于无互连线逆变器并联的多环控制方法 针对传统逆变器无线并联系统稳态均流精度低和动态响应差等缺点，提出基于传统无 线并联下垂法的新型多环控制结构，分析了逆变器并联系统有功和无功功率的环流模型。( In this paper, a novel control scheme is presented, which is able to improve the transient response and power sharing accuracy of parallel-connected inverters with no control interconnections, and the active and reactive circulating current of the parallel system model are analyzed. A multiple-loop controller is developed based on the traditional droop method. )

Matlab code for h.264 encoding. Its based on operation on I and P frames. Best working code.

matlab中文帮助文档,MATLAB教程,初学者必看的文档。(Chinese help documentation matlab, MATLAB tutorial, beginners must see the document)

basic OFDM model using simulink. This will evaluate the BER performance of OFDM of IEEE802.16 architecture. This simulation uses multipath fading channel

利用MATLAB实现在图像中嵌入和提取文本信息，最简单的LSB算法实现，自己写的可用。适合初学者(The realization of the embedded text information in the image using MATLAB, LSB algorithm to achieve the most simple, write their own use. Suitable for beginners)

RT（快速扩展随机树）是一种基于采样的算法求解路径规划问题。RRT提供可行的解如果时间RRT趋于无穷大。 RRT *是一个基于采样的算法为解决运动规划问题，这是一个概率最优变异性。RRT *收敛到最优解的渐近。 RRT * FN是一个基于采样的算法基于RRT *。RRT * FN内在渐近收敛到最优解，然而RRT * FN实现使用更少的内存(RRT (Rapidly-Exploring Random Tree) is a sampling-based algorithm for solving path planning problem. RRT provides feasable solution if time of RRT tends to infinity. RRT* is a sampling-based algorithm for solving motion planning problem, which is an probabilistically optimal variant of RRT. RRT* converges to the optimal solution asymptotically. RRT*FN is a sampling-based algorithm based on RRT*. RRT*FN inherents asymptotical convergence to the optimal solution, however RRT*FN implements it using less memory.)

是关于OFDM中的PAPR降低方法SLM的MATLAB仿真程序(Is about OFDM PAPR reduction methods in the MATLAB simulation program SLM)

信道利用率和帧长仿真测试 matlab仿真结果(Channel utilization and frame length simulation test Matlab simulation results)

以最小二乘法进行曲线拟合 得到概率密度函数的参数(With the least squares curve fitting to get the parameters of the probability density function)