一个用MATLAB实现的贝叶斯辨识的代码

使用矢量量化的方法进行说话人识别，用matlab编写 (Vector quantization method using speech recognition, written with matlab)

RF TRANSCEIVER DIRECT CONVERSION MODEL

两个复正弦加白噪声随机过程之和。用MUSIC方法进行信号频率谱估计。(The sum of two complex sinusoidal added white noise random process.The MUSIC method is used to estimate signal frequency spectrum.)

PC码的BP解码,和传统的SC解码对比，有不错的优势(bp decoder for polar codes)

《visual c++matlab图像处理与识别实用案例精选》源码(" Visual c++ matlab image processing and recognition of practical cases selected" source)

产生GPS32颗星的CA码,共包含2个文件,gps_ca_code.m用于产生任一颗星的CA码. Gen32CACode.m用于产生32颗星的CA码(Produce the GPS32 stars of the CA code, consists of two files, gps_ca_code.m CA code used to generate any one star. Gen32CACode.m used to generate the 32 stars of the CA code)

Matlab 命令大全详细介绍了Matlab中常用函数的用法以及应用举例，包括数值计算函数、数学变换函数以及绘图函数等(The book of the usage of Matlab functions details the application of commonly used functions in Matlab and application examples, including the numerical functions, mathematical transformation functions and graphics functions and so on )

鲁棒性好，性能优越，混沌的判断指标Lyapunov指数计算,使用大量的有限元法求解偏微分方程，旋转机械二维全息谱计算的实用例程，包括轨道机动仿真、初轨计算,最大信噪比的独立分量分析算法。

川大的matlab教程，带有说明和源码，实用性强(Sichuan University of matlab tutorials, with notes and source, practical)

极限学习机（extreme learning machine）ELM是一种简单易用、有效的单隐层前馈神经网络SLFNs学习算法。2006年由南洋理工大学黄广斌副教授提出。传统的神经网络学习算法（如BP算法）需要人为设置大量的网络训练参数，并且很容易产生局部最优解。极限学习机只需要设置网络的隐层节点个数，在算法执行过程中不需要调整网络的输入权值以及隐元的偏置，并且产生唯一的最优解，因此具有学习速度快且泛化性能好的优点。(Extreme Learning Machine (extreme learning machine) ELM is an easy-to-use and effective single hidden layer feedforward neural network the SLFNs learning algorithm. 2006 by the Nanyang Technological University Associate Professor Huang Guangbin. Traditional neural network learning algorithm (BP) artificial network training parameters, and it is easy to generate a local optimal solution. Extreme Learning Machine network only need to set the number of hidden nodes, the algorithm implementation process does not need to adjust the network input weights and hidden element of bias, and only optimal solution, so the learning speed and generalization good performance advantages.)