ADABOOST_te

frequency shift keying modulation

做出数据的图谱，并用归一化、傅里叶变换进行藻种识别(photo the data,and then normalize the data and then identify them.)

源于谱分析的交通流预测，预测效果相当不错(From spectral analysis of traffic flow forecasting, prediction is quite good)

Simple Inverted Pendulum with LQR,PID SimMechanics

说明：  本人毕业设计所做的光伏并网系统模型和参考资料(I graduated from design of PV grid system model and reference materials)

东南大学模态理论课件，主要是信号的测试，测量以及激振设备等。(Southeast university courseware modal theory, signal testing, measurement and excitation equipment.)

DM9000D circuit application

本实验设计了一个《北京、南京、深圳列车查询系统》的图形用户界面。用户可以通过此界面，采用“按车站名称查询”、“按列车车次查询”和“按出发地—目的地查询”三种方式，方便地查询需要的列车信息。界面友好清新，操作方便。(The experimental design was a " Beijing, Nanjing, Shenzhen Train Enquiry System," the graphical user interface. Users can use this interface, a " query by station name" , " Query by Train Train" and " by origin- destination query" three ways to easily check in need train information. Fresh and friendly interface, easy to operate.)

将小波相邻系数相关性的降噪思想引入到冗余第2代小波中，提出了基于邻域相关性的冗余第2代小波降噪方法，该方法克服了传统阈值降噪没有考虑小波系数之间相关性的不足。(Aiming at fault feature extraction in the background of strong noise, a wavelet denoising idea by incorporating neighboring coefficients is introduced into redundant second generation wavelet case. A denoising method of redundant second generation wavelet using neighbor dependency is presented. It overcomes the deficiency of traditional thresholding approaches. In this method, an original signal is decomposed by redundant second generation wavelet, and the detail and approximation signals have the same length as the original signal. The detail signals at each scale are then processed by neighbor dependency. Finally, the approximation signal and processed detail signals are reconstructed by inverse transform of redundant second generation wavelet to realize the signal denoising. )

实验一 离散时间信号的时域表示 实验二 离散时间系统的时域表示 实验三 离散时间序列的傅立叶变换 实验四 Z变换 实验五 离散傅立叶变换 实验六 数字滤波器的结构 实验七 IIR数字滤波器设计 实验八 FIR数字滤波器设计 实验九 DSP实现(Experiment a discrete-time signal in the time domain representation Experiment two discrete-time time-domain representation of the system Experiment three discrete Fourier transform of the time series Experiments four Z-transform Experimental five discrete Fourier transform Six experimental digital filter structure Experiment 7 IIR digital filter design Experiments eight FIR digital filter design Experiments nine DSP implementation)