Rayleigh-channel-simulation

模式识别实验 研究“验证技术”未必会改善分类器的性能的情况(Experimental Study of Pattern Recognition, " verification" may not improve the classification performance of the situation)

离散傅立叶变换法实现瑞利衰落信道 参考文献The Generation of Correlated Rayleigh Random Variates by Inverse Discrete Fourier Transform(The Generation of Correlated Rayleigh Random Variates by Inverse Discrete Fourier Transform)

说明：  从国外ECC网站上找到的，可以作为初始学习的参考程序。(from abroad ECC found on the site, as the initial study of the reference program.)

卷积编码和译码全过程的MATLAB源代码，已通过实验(Convolutional coding and decoding of the entire process of MATLAB source code, has passed the experimental)

是一个常规PID控制例子(包括了系统建模部分),控制对象为直升机的俯仰轴角度控制,其数学模型为二阶传递函数.(Is an example of conventional PID control (including the system modeling part), control for the helicopter pitch angle control axis, the mathematical model for the second-order transfer function.)

MATLAB implementation of SPIHT (without Arithmatic coding stage). ％ Performance evaluation : this toolbox VS. SPIHT ％ Test image: lena512.raw ％ bpp SPIHT(dB) This code(dB) ％ 0.1000 29.8107 29.3202 ％ 0.2000 32.7202 32.2514 ％ 0.3000 34.5479 34.0331 ％ 0.4000 35.8422 35.4857 ％ 0.5000 36.8623 36.5939 ％ 0.6000 37.6650 37.3759 ％ 0.7000 38.2581 38.0491 ％ 0.8000 38.9390 38.7058 ％ 0.9000 39.5218 39.3437 (MATLAB implementation of SPIHT (without A rithmatic coding stage). Performance evalua% tion : this toolbox VS. SPIHT%% Test image : lena512.raw%% bpp SPIHT (dB) This code (dB)% 0. 1000 29.8107 32.7202 0.2000 29.3202% 32.2514% 0.3000 0.4000 34.5479 34.0331% 35.8422 35.485 7% 0.5000 0.6000 36.8623 36.5939% 37.6650 37.3 759% 38.0491% 0.7000 0.8000 38.2581 38.9390 38 .7058 0.9000 39.5218 39.3437%)

local binary pattern matlab source code

地震数据 segy 文件，读写工具 readsegy(segy tools)

为判断聚类结果质量的好坏，需要一个客观的评价指标来评价聚类结果的合理性。聚类性能评价方法通常分为三种：外部评价法，内部评价法，相对评价法。外部评价法将聚类结果得到类标签和已知类标签进行比较，此评价法的前提是数据集样本的类标签已知(In order to judge the quality of clustering results, good or bad, the need for an objective evaluation to assess the reasonableness of the clustering results. Clustering performance evaluation method is usually divided into three types: external evaluation method, internal evaluation method, relative evaluation method. External evaluation method of clustering results to obtain class labels and the known class labels are compared, the premise of this evaluation method is a class label known sample of the data set)

遗传算法的优化计算—— -建模自变量降维(Genetic Algorithm optimization model - argument dimensionality reduction)