bcc

DFT进行频谱分析时的三种现象 1、混叠：对连续信号采样，要求连续信号是带限的，采样频率要足够高。Fs应满足Nyquist采样定理才不产生混叠。 采样前加低通滤波器防混叠 2、频谱泄漏：DFT对时域信号进行了截断（相当于采样信号乘了一个窗函数），时域的乘积相当于频域卷积，改变了原信号频谱。 改用其他窗函数（非矩形）改善泄漏。 3、栅栏现象：DFT 只给出了频谱在采样点上的取值，采样点间的频谱内容丢失。(DFT spectrum analysis of a three phenomena, aliasing : continuous signal sampling, requiring continuous signal is band-limited, the sampling frequency should be high enough. Fs meet the Nyquist Sampling Theorem would not have aliasing. Sampling former low-pass filter plus anti-aliasing 2, spectrum leakage : DFT right time domain signal a disconnect (equivalent to a sampling signal by a window function). time domain is equivalent to the product of frequency-domain convolution, changes in the spectrum of the original signal. Window functions to switch to other (non-rectangular) to improve leakage. 3, fenced phenomenon : DFT spectrum is given only at the sampling point value, sampling points of the spectrum as lost.)

Folding coefficient technique for DWT

说明：  运动载体的定位与导航一般应用Kalman滤波算法。可 靠的Kalman滤波算法要求有可靠的函数模型、随机模型以 及合理的估计方法。实际情况中运动载体一般难以确保规 则运动，因而精确的函数模型的构造十分困难。近年来， 有不少学者对机动载体运动模型进行了讨论，所属内容各 具特点，建立的各种模型包括微分多项式模型、常速度模 型、常加速度模型、时间相关模型，半马尔柯夫模型、 Noval统计模型及机动载体的“当前”统计模型(Moving vehicle positioning and navigation general application of the Kalman filter algorithm. Kalman filter algorithm requires a reliable function model, a stochastic model, as well as a reasonable estimation method. Moving carrier in the actual situation is generally difficult to ensure a regular motion, and thus the the precise function model structure is very difficult. In recent years, many scholars have discussed the movement of the motor carrier model, each with distinct characteristics of their respective content, establish various models including the differential polynomial model, constant velocity model, constant acceleration model, time-dependent model, semi-Markov model, Noval statistical model and motor carrier &quot current&quot statistical model)

基于bandelet去噪的测试函数,并用信噪比进行评估(It is used for testing the Bandelet denoising)

MIMO 信道估计是恢复MIMO信号的重要途径，一篇文献阐述一种新的MIMO信道估计算法，很有借鉴价值(MIMO channel estimation is an important way to restore MIMO signal, a literature describes a new MIMO channel estimation algorithm, a very useful reference value)

Change in Angle, Feature of Shapes & Characters

Arduino 中关于寄存器的相关修改规则及方法(Arduino register relevant changes regarding rules and methods)

仿真风电场并网时电力网络发生短路故障时的状态(Short circuit in power network simulation of wind farms when the state)

Bootstrapping Fuzzy-GARCH Regressions on the Day of the Week Effect in Stock Returns

用Matlab实现了常见的几种滤波算法：中位值滤波，递推平均滤波，一阶滞后滤波等算法。可以直接运行(Using Matlab to achieve several common filtering algorithms: median filtering, average filtering recursive, first-order lag filtering algorithm. Can run)