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说明：  关于gauusian函数的matlab代码，角点提取时会用到(About gauusian function matlab code that will be used corner detection)

this is matlab code to solve l1decode problem!!!

详细介绍了matlab插值与拟合方法，包括拉格朗日多项式插值、牛顿插值、分段线性插 值、Hermite 插值和三次样条插值和曲线的最小二乘拟合、多项式拟合方法、最小二乘优化所有程序均有相应的说明与应用实例(Details of the matlab interpolation and fitting methods, including Lagrange polynomial interpolation, Newton interpolation, piecewise linear interpolation Value, Hermite interpolation and cubic spline interpolation and least-squares curve fitting, polynomial fitting method, least squares optimization program has all the appropriate instructions and application examples)

Digital filter implementation examples

matlab基础教程，对每个部分进行详细介绍并通过举例说明，对初学者很有帮助！(Matlab basic course, to each part is introduced and through for example, for beginners helpful! )

希尔伯特黄变化学习总结，技术文档，含部分matlab代码，希望对大家有帮助(Hilbert Huang change learning summary, technical documentation, containing part of the matlab code, and hope to help everyone)

This code is related to the course Digital Communications. It makes a simple communication system which uses AWGN and QPSK

无线传感网络一种分布式定位算法的简介，介绍详细，并带有MATLAB仿真。(A distributed wireless sensor network localization algorithms brief description in detail, and simulation with MATLAB.)

to find the blood cell using image processing

：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.)