EII1

Matlab图形的程序等练习，有需要的下吧吧用积分(Matlab graphics program such as exercise, there is a need to let it use the next integral)

Efficiency optimization of IPMSM with PI controller and loss minimization algorithm. Good for comparison and simulation results.

afhkds lsfjk sd jsk nff lakd f

A MIMO multiplexing system with NT transmit and NR = NT receive antennas is designed. The main challenge for MIMO systems lies in the non-orthogonality of the transmission channel. This can be solved by turbo processing. Turbo channel encoder is used for converting the bits in its suitable form. Then different M-ary QAM is compared.

For the first time In Croatia an airborne application of hyperspectral imaging was introduce under recent technologic project "System for the Multisensor Airborne Reconnaissance and Surveillance in the Crisis Situations and the Environment protetion"

基于麦克风阵列的声源定位方法很多，相位变换加权的可控响应功率SRP-PHAT声源定位算法在混响环境中有较强的鲁棒性，可实现真实环境中的声源定位，因此该算法得到了广泛应用。SRP-PHAT对阵型没有特定要求，因此也适用于分布式阵列，事实上很多基于分布式阵列的定位系统采用了该算法。(This function creates an acoustic image from a set of microphone array signals using a steered response power (SRP algorithm).This particular version uses only integer shifts on the input signals for the delay and sum operation, and computes the coherent average power (rather than total average power), which does not include the power terms for each individual microphone signal. So the coherent power is effectively the cross-correlation between different microphone signals without the self power terms, and can therefore be negative.)

说明：  Anova analysis for vibration

LDPC(Low-density-parity-check，低密度奇偶校验)码是一类具有稀疏校验矩阵的线性分组码，不仅有逼近Shannon限的良好性能，而且译码复杂度较低，结构灵活，是近年信道编码领域的研究热点(LDPC (Low-density-parity-check, low-density parity check) codes are a class of sparse check matrix of linear block codes, is not only good performance approaching Shannon limit, and the decoding complexity low, flexible structure , the field of channel coding in recent years the research focus)

BP神经网络用于分类与回归的matlab源码 注释很详细(1、NeuralNetwork_BP_Classification.m- 分类 2、NeuralNetwork_BP_Regression.m- 回归 )

Blind signal seperation method using maximum likelyhood method