matlab-femcode

bayesian classifier for 2 class

SVM multiclass classifier

双极性码元的误比特率计算，画出误比特率曲线。(bipolar symbol of the bit error rate calculation, to give the BER curves.)

转矩计算模块，输入包括三相电流ia ib ic，电动势ea eb ec，输出为转矩、转速。(Torque calculation module, the input including the three-phase current ia ib ic, emf ea eb ec, output torque, speed.)

Some logic stuff. for example Recursive Pi calculation. Part of Thesis at the TH-Nuernberg

本代码主要提供了在频域使用fastica进行盲源分离，并且解决了频域的排列和增益两个歧义性问题。(This code mainly provides the use of fastica in the frequency domain for blind source separation, and solves the frequency domain arrangement and gain of two ambiguity problems.)

matlab是实现通信理论及应用的很有用的一个工具，本文会给你很多启发(matlab is to achieve communication theory and application of a very useful tool, this article will give you a lot of inspiration)

单个的MIMI-OFDM系统的MATLAB的仿真，有英文注释(Single MIMI-OFDM system MATLAB simulation, with English notes)

Structural instability study of laminated composite plates due to fluid structure interaction

本文采用小波神经网络进行交通流量预测，短时交通流量存在随机性和非线性因素，影响预测的准确性。传统预测模型难以反映交通流量变化特点，同时传统神经网络易陷入局部极小值，泛化能力差，交通流量预测精度低。为了提高短时交通流量预测精度，提出一种小波神经网络的短时交通流量预测模型。小波神经网络可以对短时交通流量随机性、不确定性进行局部分析，并进行非线性预测，验证了模型的有效性，进行了对比试验。验证结果表明，小波神经网络提高了短时交通流量预精度，预测结果更具应用价值。(In this paper, wavelet neural network is used to forecast traffic flow. There are random and nonlinear factors in short-term traffic flow, affecting the accuracy of prediction. The traditional prediction model is difficult to reflect the characteristics of traffic flow changes. At the same time, the traditional neural network is easy to fall into the local minimum, the generalization ability is poor, and the prediction accuracy of traffic flow is low. In order to improve the accuracy of short-term traffic flow forecasting, a short-term traffic flow prediction model based on wavelet neural network is proposed. The wavelet neural network can analyze the randomness and uncertainty of short-term traffic flow and perform nonlinear prediction. The validity of the model is verified and a comparative experiment is conducted. The verification results show that the wavelet neural network improves the short-term traffic flow pre-precision, and the prediction result has more application value.)