System-Identification

Business Economics & Finance with Matlab GIS and Simulation Models

M/M/1单服务台排队系统仿真（用事件调度法实现离散事件系统仿真） 顾客到达模到达时间间隔和顾客服务时间均服从负指数分布，单服务台系统，按照单队排队，按FIFO方式服务。考察服务n个顾客（n=1000，2000，3000，5000）后的顾客平均队长及平均排队等待时间。(M/M/1 single-server queuing system simulation (using Event Scheduling Method Discrete Event Simulation System) to customers Da-mo arrival time interval and customer service time are negative exponential distribution, single-desk system, in accordance with the single-team queue, by FIFO mode services. N inspection services customers (n = 1000,2000,3000. 5000) the average customer captain, and the average queue time.)

the maximum rate in function of the 02 probablity of detection and false alarm

single phase active power filter and may also contain images and documents relative to filter control

Display fft. A fast Fourier transform (FFT) is an algorithm to compute the discrete Fourier transform (DFT) and its inverse.

可以在多尺度熵对时间序列进行复杂性度量。较近似熵、样本熵好(Multiscale entropy can be time-sequence complexity metrics. Better than approximate entropy, sample entropy )

最小二乘支持向量机,用于多元非线性回归分析,非线性拟合与预测(Least squares support vector machine for multi-linear regression analysis, nonlinear fitting and prediction)

求图像二维灰度直方图的matlab程序,讲述了如何用MATLAB去编写二维灰度直方图.(Seeking two-dimensional gray scale image histogram matlab program, describes how to use MATLAB to write two-dimensional histogram.)

Lohmann3的一个全息图编码，能运行和出现正确的结果，含图(Lohmann3 a hologram coding, can run and the emergence of the correct result)

：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.)