P0701

用显示euler法、heun法、中点法和rk4方法求解一阶微分方程精确解和数值解的程序(Euler method with the show, heun method, midpoint method and rk4 exact method for solving first order differential equations and numerical solutions of the procedures)

产生噪声调幅干扰信号，并画出时域和功率谱 (AM interference signal noise, and draw the time domain and power spectrum)

MATLAB/SIMULINK下建立发电机仿真模型(Generator simulation model established under MATLAB/SIMULINK)

主要内容有：雷达数据处理概述（包括研究目的、意义、历史和现状等），参数估计与线性滤波方法，非线性滤波方法，量测数据预处理技术，多目标跟踪中的航迹起始，极大似然类多目标数据互联方法，贝叶斯类多目标数据互联方法，机动目标跟踪，群目标跟踪，多目标跟踪终结理论与航迹管理，无源雷达数据处理，脉冲多普勒和相控阵雷达数据处理，雷达组网数据处理，雷达数据处理性能评估，雷达数据处理仿真技术，雷达数据处理的实际应用，以及关于雷达数据处理理论的回顾、建议与展望。(The main contents are: an overview of the radar data processing (including research purpose, meaning, history and current status, etc.), parameter estimation method with linear filtering, nonlinear filtering method, measurement data preprocessing techniques, starting track multiple target tracking, maximum Likelihood class of multi-target data interconnection methods, Bayesian methods class multi-target data association, target tracking, target tracking group, multi-target tracking end theory and track management, passive radar data processing, pulsed Doppler and phased array radar data processing, radar network data processing, radar data processing performance evaluation, radar data processing simulation technology, the practical application of radar data processing, as well as a review on radar data processing theory, suggestions and prospects.)

使用矩形窗函数，分析信号截短对离散傅立叶变换的影响，其中原始信号为正弦函数(Use a rectangular window function, the analysis of the signal truncated discrete Fourier transform, which the original signal is a sine function)

合成孔径雷达成像算法中的点目标条带成像算法，给需要的人(Synthetic aperture radar imaging algorithm of point target band imaging algorithm, to those who need)

说明：  使用MATLAB进行的SIMULINK仿真，实现了磁悬浮PID控制(SIMULINK simulation with MATLAB realizes the PID control of magnetic levitation)

The accompanying matlab code demonstrates how to separate three mixtures of three signals which have arbitrary pdfs

Matlab with acoutics

A discrete cosine transform (DCT) expresses a finite sequence of data points in terms of a sum of cosine functions oscillating at different frequencies. DCTs are important to numerous applications in science and engineering, lossy compression of audio (e.g. MP3) and images (e.g. JPEG) (where small high-frequency components can be discarded), to spectral methods for the numerical solution of partial differential equations. The use of cosine rather than sine functions is critical for compression, since it turns out (as described below) that fewer cosine functions are needed to approximate a typical signal, whereas for differential equations the cosines express a particular choice of boundary conditions.