文献实现的kalman滤波器的设计源程序

Not mine code, but very usefull!

这是一个四个不同的S函数实现集合的递归模糊神经网络（RFNN）。该网络采用了4组可调参数,这使得它非常适合在线学习/操作，从而可应用到系统识别等方面。(This is a collection of four different S-function implementations of the recurrent fuzzy neural network (RFNN) described in detail in [1]. It is a four-layer, neuro-fuzzy network trained exclusively by error backpropagation at layers 2 and 4. The network employs 4 sets of adjustable parameters. In Layer 2: mean[i,j], sigma[i,j] and Theta[i,j] and in Layer 4: Weights w4[m,j]. The network uses considerably less adjustable parameters than ANFIS/CANFIS and therefore, its training is generally faster. This makes it ideal for on-line learning/operation. Also, its approximating/mapping power is increased due to the employment of dynamic elements within Layer 2. Scatter-type and Grid-type methods are selected for input space partitioning.)

文件包里面包含感应加热电源的simulink仿真文件，和一个matlab源文件用于追踪感应加热的谐振点。(Package which contains induction heating power supply simulink simulation files, and a matlab source files used to track the resonance point of induction heating.)

Fourie series. Waves with sines and cosines. Square wave, sawtooth wave, etc. Very usefull.

基于S函数BP神经网络的PID控制器的研究与学习，方便简单，实用性特别强。(S function based on BP neural network PID controller research and study, convenient and simple, practical particularly strong.)

七自由度冗余机械臂的阻抗控制，并实现自动对奇异构型的避免，通过设置性能指标，自动对机械臂此时性能指标的变化进行判断并修正机械臂轨迹(The impedance control of the seven degree of freedom redundant manipulator is realized, and the automatic configuration is avoided. By setting the performance index, the change of the performance index of the robot arm is automatically judged and the trajectory of the manipulator is corrected)

MIMO和OFDM技术是B3G（LTE、LTE-A、4G）的关键物理层技术，该书详细介绍了该领域的概念和理论，并通过MATLAB程序进行仿真和验证。该书共分13章，分别为：无线信道：传播与衰落，SISO信道模型，MIMO信道模型，OFDM介绍，OFDM同步技术，信道估计，PAPR（峰均比）减小技术，小区间干扰消除技术，MIMO：信道容量，天线分集和空时编码技术，空分复用MIMO系统的信号检测，在发射端利用信道状态信息，多用户MIMO。

阐述了负荷预测的应用研究,用MATLAB实现动态聚类或迭代自组织数据分析，采用了小波去噪的思想，多抽样率信号处理，利用自然梯度算法，预报误差法参数辨识-松弛的思想，进行逐步线性回归，从先验概率中采样，计算权重。( It describes the application of load forecasting, Using MATLAB dynamic clustering or iterative self-organizing data analysis, Using wavelet denoising thought, Multirate signal processing, Use of natural gradient algorithm, Prediction Error Method for Parameter Identification- the idea of relaxation, Stepwise linear regression, Sampling a priori probability, calculate the weight.)

IT IS A DOCCUMENT ABOAT REACTIVE POWER

有关OFDM信号的处理问题，包括检测等内容(sth. about OFDM)