enerpot

说明：  计算循环卷积，DFT，IDFT,FFT... .. (Computing cyclic convolution, DFT, IDFT, FFT ... ..)

LEACH协议的改进程序，有总剩余能量的分析图(LEACH agreement improvement program, have total surplus energy were)

关于矩阵的一些运算,大家可以参考一下,(Some calculations on the matrix, we can refer to,)

Keyou You, Nan Xiao, Lihua Xie Analysis and Design of Networked Control System

Matlab的窗函数_矩形窗_三角窗_汉明窗_汉宁窗_布莱克曼窗(Matlab window function _ rectangular window _ triangular window _ _ _ Han Hanning window, Hamming window Blackman window)

create a function in neural network

利用混沌系统给图像加密，加密方法简单易懂，对初学者很好理解(Image encryption using chaotic systems ，encryption method is simple and easy to understand, good for beginners to understand)

matlab music经典算法 2源信号，入射角为0 45°进行DOA估计(algorithm of music（multiple signal classification）)

This it the code to describe rayleigh distribution

：该文把局部三值模式(Local Ternary Patterns, LTP)纹理特征引入Mean Shift 跟踪算法，提出了基于多 特征的Mean Shift 人脸跟踪算法以解决Mean shift 跟踪算法的鲁棒性问题。通过对LTP 纹理特征的分析、研究， 提出了一个LTP 关键纹理模型，既增强了目标的关键纹理信息，又简化了LTP 纹理模型。在此基础上，提出一 种基于LTP 关键纹理特征和肤色特征的Mean Shift 人脸跟踪算法，有效地解决了Mean Shift 算法的鲁棒性问题。 为进一步提高对快速运动目标的跟踪速度和跟踪性能，该文引入了卡尔曼滤波器对目标进行预测。实验结果表明， 该文的算法在目标定位的准确性和跟踪性能上比Mean Shift 算法均有明显的提高。(: In this paper, the texture characteristics of the local ternary patterns Local Ternary Patterns (LTP) Mean Shift tracking algorithm proposed Mean Shift face tracking algorithm based on multiple features in order to solve the Mean shift tracking algorithm robustness. Texture characteristics of LTP analysis, research, a key LTP texture model, not only enhanced the key goal of texture information, but also simplifies the the LTP texture model. On this basis, based on the LTP key texture features and color characteristics Mean Shift face tracking algorithm, effectively solved the robustness of the Mean Shift algorithm. To further enhance the fast-moving target tracking speed and tracking performance, this paper introduces the Kalman filter to predict the target. The experimental results show that the algorithm of the text in the target positioning accuracy and tracking performance than the Mean Shift algorithm to significantly improve.)