搜索资源列表
AR_example
- 时间预测模型AR，AR模型的算法，对数据进行预测。-Time prediction model AR, AR model algorithm, the data to predict.
EMDthenAR
- 对数据先进行经验模态分解得到不同特征尺度的信号分量，然后对所有的信号分量用AR模型进行预测得到预测后的分量，然后将预测后的分量进行重构得到最终的预测信号。-The data first empirical mode decomposition characteristics of the signal components of different scales, and then for all signal components obtained by AR model to predict
rsd1
- 单频加白噪声的随机信号分析模型，包括经典的周期图法和AR模型-Add single-frequency white noise random signal analysis model, including the classic periodogram and AR model
prediction-methods-for-hydrology
- 径流预报常用的几种模型：AR模型，BP模型，RBF模型，GM(1,N)模型；预报数据预处理方法：自相关函数以及偏自相关函数确定法；EMD方法-Several commonly used runoff forecasting model: AR model, BP model, RBF model, GM (1, N) model forecast data preprocessing methods: autocorrelation function and partial autocorre
arma_model
- 时间序列建模-ar模型，arma建模,消除周期趋势-Time series modeling-ar model, arma modeling, eliminate cyclical trends
ARburg
- AR模型参数BURG算法估计的功能函数及源代码-BURG AR model parameter estimation algorithm performance function and source code
ls_ar
- 自编函数实现AR模型的最小二乘估计-AR model to achieve self-function least squares estimation
ARMAPmodel
- 时间序列AR模型建立matlab源代码。一个正弦型号叠加正太白噪声信号作为系统输入-Time series AR model matlab source code. Taebaek a sinusoidal model superimposed noise signal being input as the system
ARmodel
- 生成一个正弦信号，使用levinson-durbin算法和最终预测阶数准则FPE估计其AR模型的阶数，并且通过解Yule-Walker方程求得AR模型的参数，进而求得该正弦信号的功率谱-Generating a sinusoidal signal, using levinson-durbin algorithm to predict the order and final order of the criteria FPE estimates its AR model and AR model
TVAR_matlab
- 用于时变结构的AR模型建立，即TVAR 的matlab程序-AR model for time variable structure established that TVAR matlab program
spectrum_estimate
- 本程序可以实现基于AR模型的谱估计，具有较强的适用性-The program can achieve spectral estimation based on AR model has strong applicability
Levinson-durbin.ZIP
- 用Levinson方法实现功率谱密度的估计。在N=1024条件下调试程序过程中用Levinson-Durbin快速递推法得出的图形不稳定，每次调试结果都不大相同，AR模型的阶次应选择在N/3<P<N/2之间，式中的N是记录的数据长度，这样可以得到高分辨率的估计谱，并且很少出现伪峰。-Levinson method used to achieve power spectral density estimate. Commissioning conditions under N = 10
System-identification
- 用Matlab实现自适应信号处理中的系统辨识，自适应处理器采用自适应线性组合器，未知被控系统采用AR model。用了LMS算法和最速下降法实现。-Realise system identification in adaptive signal processing with matlab.The LMS algorithm and Speedest Descent method are used.
ARmodel
- 利用时间序列处理方法AR模型进行信号谱估计，相对于传统的FFT的方法，分辨率更好，峰值更尖锐-Processing method using time series AR model spectrum estimation signal, relative to traditional methods of FFT resolution better, sharper peaks
AR
- AR预报模型 Fortran算法 具有很大实用性-AR forecasting model Fortran algorithms
Frequency_HRV
- 利用AR模型和Lomb算法的心率变异性分析。-Analyzed using AR model and Lomb algorithm HRV.
ARprediction
- 对序列建立AR模型，并以概率形式给出预测数列表达。先进行平稳性检验后求取自相关函数，用Y-W法求取模型参数，并应用FPE准则确定阶数，进行预测后，给出概率表达。-AR model for the sequence established, and the probability forecast given in the form of a list. After a smooth first autocorrelation function test strike strike model p
VBAR
- 准确混合噪声的成分,使AR模型的使用范围更为广泛。-Accurate mixing noise ingredients to make use of a wider range of AR model.
spectrum-estimation
- 功率谱估计是利用有限长的数据估计信号的功率谱，广泛应用于各个领域。功率谱估计主要分为经典谱估计与现代谱估计。常用的经典谱估计方法有周期图法，相关法，周期图的改进法，常用的现代谱估计方法有最大熵谱估计，AR模型，MA模型，ARMA模型。经典谱估计适用于长序列的信号，其主要缺陷是描述功率谱波动的数字特征方差性能差，频率分辨率低，现代谱估计适用于短序列的信号，旨在改善谱估计的分辨率，并将其应用于实际地震资料的谱分析。 -Power spectrum estimation is the use of
xizaipufenxi
- 包含了两种现代谱分析方法，即AR模型法与bartlett法，对信号的分析有重要作用。-Contains two modern spectral analysis method, namely the AR model law and bartlett method for analyzing signals an important role.