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KALMTOOL工具箱2.0版，包含Kalman滤波器的仿真程序和对应的C文件。(KALMTOOL Toolbox version 2.0. Kalman filter contains the simulation program and the corresponding C document.)

说明：  LTE-A中的AF和DF中继研究，比较有用(LTE-A in the AF and DF relaying research, more useful)

打开Matlab，输入代码，执行，得结果(Open Matlab, input code, the implementation of the findings)

说明：  飞行器姿态角的欧拉角表示方法与余弦矩阵表示方法的matlab转换程序(Aircraft attitude angle of the Euler angle method with cosine matrix methods matlab conversion process)

(2,1,3)卷积码编码，软判决译码；matlab语言编码；verilog语言译码；((2,1,3) convolutional code encoding, soft-decision decoding matlab coding verilog decoder )

Machine learning 在线课程 exercise1(Machine learning online courses exercise1)

本文采用模糊数学和优化理论建立起一套预测模型由计算机自动预测电力负荷从而保证了预测结果的正确性和可信度通过对深圳市远景年电量预测的实例表明该方法是可行而有效的 (this fuzzy optimization theory and mathematical model to establish a set automatically by a computer forecasting electricity load so guarantee the accuracy of the results and credibility of the Shenzhen City Vision, electricity demand forecasting examples show that the method is feasible and effective)

包括轨道机动仿真、初轨计算,利用最小二乘算法实现对三维平面的拟合，实现了对10个数字音的识别。( Including orbital maneuvering simulation, initial orbit calculation, Least-squares algorithm to fit a three-dimensional plane, To achieve the recognition of 10 digital sound.)

In this paper, we show how support vector machine (SVM) can be employed as a powerful tool for $k$-nearest neighbor (kNN) classifier. A novel multi-class dimensionality reduction approach, Discriminant Analysis via Support Vectors (SVDA), is introduced by using the SVM. The kernel mapping idea is used to derive the non-linear version, Kernel Discriminant via Support Vectors (SVKD). In SVDA, only support vectors are involved to obtain the transformation matrix. Thus, the computational complexity can be greatly reduced for kernel based feature extraction. Experiments carried out on several standard databases show a clear improvement on LDA-based recognition

一本详细介绍matlab功能的书，很适合初级的学习者，高手请绕行(A detailed introduction matlab function of the book, it is suitable for junior learners, experts please bypass)