N_FINDR

Classic data mining book

无限状态隐马尔可夫模型(IHMM)采样与推理算法程序,可用于模式识别,视频异常事件检测等,开发平台了最新的MATLAB2009(Infinite state Hidden Markov Model (IHMM) sampling procedures and the reasoning algorithm can be used for pattern recognition, video detection of abnormal events such as the development platform, the latest MATLAB2009)

pdf文档，一种改进的OFDM最大似然符号同步算法。利用导频符号与循环前缀的最大似然算法进行联合同步检测,并可以纠正符号偏差。(An improved symbol synchronization algorithm for OFDM systems is proposed in this paper.)

无迹卡尔曼滤波UKF是重要的非线性滤波方法。它采用UT变换的方法，不再近似系统的非线性方程，它仍然用高斯随机变量表示状态分布，不过是用特定选择的样本点加以描述，每个点叫一个高斯点，它从系统状态的概率密度函数中取出；然后，按系统的真实模型演化，得到非线性演化后的σ点，使得样本均值和样本方差是真实均值和真实方差的好的近似。 在这个程序中，实现了基于UKF的滤波方法，并且建立了两种仿真环境进行实验。(Unscented Kalman filter UKF is an important nonlinear filtering method. It uses the UT transformation method, no similar system of nonlinear equations, it still says the state with the Gaussian distribution of random variables, but the specific choice is to describe the sample points, each point is called a Gaussian point, it is from probability density function of the system state to remove then, according to the true model of evolution of the system obtained after the nonlinear evolution of σ point, making the sample mean and sample variance is true variance of the mean and the true good approximation. )

本代码根据noiselets算法编写，可以生成NXN的任意矩阵(To write the code according to the noiselets algorithm, you can generate an arbitrary matrix of NXN)

小波神经网络研究的进展用于预测和函数逼近，希望可以抛砖引玉(Wavelet neural network for predicting the progress of the study and function approximation, hoping to start)

粒子群PID参数自整定算法，简单易行，能够使用。(Particle swarm PID parameter auto-tuning algorithm, simple and can be used.)

说明：  用于求解高速球轴承的非线性方程组，输入主程序，用fsolve，可以直接解出来(Nonlinear equations used to solve high-speed ball bearings, input the main program, with fsolve, can be solved directly.)

仿真了OFDM中的SLM方法 ，并附有仿真图形，对于初学PAPR的朋友可有用(Simulation of the OFDM in the SLM method, together with simulation graphics, for a friend can be useful for beginners PAPR)

Principal Component analysis comparision with PLS method.