"Matlab常用算法程序: 时间序列预测算法"

The "matlab的一些常用算法.pdf" contains a collection of commonly used algorithms in MATLAB, including the time series prediction algorithm based on the mean generating function. The program consists of three main components: predict_fun.m, timeseries.m, and seriesexpan.m. The predict_fun.m serves as the main program, while timeseries.m and seriesexpan.m are the subroutines called within the main program. The predict_fun.m program takes two input parameters, b and step, which represent the training data and the number of prediction data, respectively. It then calculates the mean and standard deviation of the training data and normalizes it using the mean and standard deviation. Following this, the program calls the timeseries.m subroutine to generate the time series of the normalized training data. The seriesexpan.m subroutine is then called to expand the series for the specified number of prediction data points. The output of the predict_fun.m program is the predicted data, stored in the variable ima_pre. The program utilizes the mean and standard deviation of the training data to normalize it, and then uses the timeseries.m and seriesexpan.m subroutines to generate the time series and expand the series for prediction, respectively. Overall, the algorithm and program provided in "matlab的一些常用算法.pdf" offer a comprehensive and efficient method for time series prediction based on the mean generating function. The program is well-structured and utilizes subroutines to modularize the code, making it easier to understand and maintain. By following the steps outlined in the program, users can accurately predict time series data based on the training data provided. This makes it a valuable resource for researchers and practitioners working with time series analysis in MATLAB.