搜索资源列表
Time
- Time series analysis and prediction
ECGSYNC-physionet
- ECGSYN generates a synthesized ECG signal with user-settable mean heart rate, number of beats, sampling frequency, waveform morphology (P, Q, R, S, and T timing, amplitude,and duration), standard deviation of the RR interval, and LF/HF ratio (a measu
BPN
- Backpropagation Network Time-Series Forecasting 源码, 经典的BPN人工神经网络例子源码-Backpropagation Network Time-Series Forecasting source, the classic example of artificial neural network BPN source
multi-serialsport
- 基于多线程串口通信的生产数据实时采集系统，对系统在实现中涉及的多线程处理技术、串行通信、数据库访问技术和Socket 通信技术作了较为详尽的说明-Based on multi-threaded serial communication in real-time production data acquisition system, the system involved in the realization of multi-threaded processing technology, ser
time
- 数模用的时间序列模型，要用matlab编程-Model with time-series model, using matlab programming
Loren_Chaos_serises
- 产生Lorenz混沌序列,为下一步非线性时间序列研究打下基础-Construct Lorenz chaotic seris for the research of nonlinear time series.
ForcedPendulum
- This simulink model simulates the damped driven pendulum, showing it s chaotic motion. theta = angle of pendulum omega = (d/dt)theta = angular velocity Gamma(t) = gcos(phi) = Force omega_d = (d/dt) phi Gamma(t) = (d/dt)omega + omega/Q
shijianxulie
- 时间序列的时频特性分析研究时间序列的傅里叶变换及逆变换，快速梅林变换及逆变换，短时离散傅里叶变换，得到瞬时频率。 研究时间序列的Born–Jondan时频分布图，Butterworth时频分布图，Choi–Williams时频分布图，得到瞬时频率。 -Time series analysis of time-frequency characteristics of time series of Fourier transform and inverse transform, the fa
autorelation_function_to_obtain_the_delays_of_time
- 自相关法求取时间序列延时的函数，包括Simulink产生时间序列的文件，两个主函数，以及运行程序-Since the correlation function to obtain time series of delay, including time series generated Simulink file, the two main functions, and operational procedures
time
- 时间序列进行平稳性检验然后利用aic准则选取合适的模型进行一步预报。-Stationary time series of test criteria and then select the appropriate use of aic step model prediction.
time-toolbox
- 这是一个时间序列分析程序包 这是一个时间序列分析程序包-This is a time series analysis package is a time series analysis package
AR
- 时间序列模型建立 损伤识别(Damage identification by time series model)
SAS-base tutorial
- 如果想考取SAS证书的话，里面有三本参考资料，非常全面。(Financial Time Series)
Dissertation-ARIMA_SVR-prediction-master
- 基于时间序列分析ARIMA和SVR组合模型的预测(Prediction of ARIMA and SVR combined models based on time series analysis)
LSTM-for-time-series-prediction
- 本代码是使用lstm进行时间序列预测，能够很清晰的说明如何使用lstm(Time series prediction using LSTM)
金融时间序列分析-英文版
- 金融时间序列分析（英文版）-Ruey S.Tsay所著，第三版(Financial time series analysis (English version) -Ruey S.Tsay, Third Edition)
time-series-forecasting-keras-master
- 基于ARIMA模型和LSTM模型，提出一种高性能得时间序列预测算法(Based on ARIMA model and LSTM model, a high performance time series prediction algorithm is proposed.)
23_time_series_prediction
- 用 Python 机器学习，时间序列模型预测， 循环神经网络(Python Machine Learning, Time Series Model Prediction, recurrent Neural Network)
R时间序列初探
- 时间序列分析以及实现，初步了解如何用R实现时间序列分析(time series analysis with R and its application)
时间序列分析——基于R（第2版）习题数据
- 时间序列分析r语言练习数据。时间序列分析(Time-Series Analysis)是指将原来的销售分解为四部分来看——趋势、周期、时期和不稳定因素， 然后综合这些因素， 提出销售预测。强调的是通过对一个区域进行一定时间段内的连续遥感观测，提取图像有关特征，并分析其变化过程与发展规模。当然，首先需要根据检测对象的时相变化特点来确定遥感监测的周期，从而选择合适的遥感数据。(Time series analysis is to decompose the original sales into fo