Below are the order details, additional documents will be provided upon approval.
The work has to be done at Matlab code
Paper topic: New Method to Increase the Accuracy and the Clarity FOR Empirical Mode Decomposition
Paper style: Other
Language style: English (U.S.)
Type of work: Writing from scratch
Paper type: Thesis
Number of pages: 60
Number of sources: 3
Amount: $330 USD
Order instructions: Using moving average method in the Empirical Mode Decomposition .. Moving average, also called rolling average, rolling mean or running average, is a type of finite impulse response filter used to analyze a set of data points by creating a series of averages of different subsets of the full data set. Given a series of numbers and a fixed subset size, the first element of the moving average is obtained by taking the average of the initial fixed subset of the number series. Then the subset is modified by \\\"shifting forward\\\"; that is, excluding the first number of the series and including the next number following the original subset in the series. This creates a new subset of numbers, which is averaged. This process is repeated over the entire data series. The plot line connecting all the (fixed) averages is the moving average. A moving average is a set of numbers, each of which is the avearge of the corresponding subset of a larger set of datum points
. A moving average may also use unequal weights for each datum value in the subset to emphasize particular values in the subset. The main approach of this method is to remove the low frequency part first and gradually move to higher frequency parts.