How to pre-process training data, the x-y coordinates data represent the Gaussian graphs for ANN training?

4 次查看(过去 30 天)
Hi all, I am trying to train a network to produce the Sigma value and Delta value of the Gaussian & Dual-dirac delta. The inputs is the x-y coordinates of the Gaussian plots. every plot represent certain value of Sigma & delta.
Now due to the range of Sigma & delta, there're a lot of redundant x-y pairs and causing a lot of noise for the training data.
I am trying to just extract the enough "meaningful" N numbers of x-y coordinates per plot to feed to the ANN for training. and still need to maintain the same training data array dimensions for every plots.
For eg: To generate M numbers of plots for the training (i have this function ready), and N x-y pairs per plots The input training data array dimension will be NxM. the Target training data array dimension will be 2xM.
Example of the plots as follows: and the Input training Raw data of the X-Y coordinate are stacked as the attached spreadsheet which consists of many "near to Zeros" coordinates. </matlabcentral/answers/uploaded_files/126265/gauss.PNG>
My current problem are:
1. How to pre-process the training data or sample the meaningful plots with same N number of X-Y coordinates, for a M numbers of plots (may have few hundreds plots)? PS: I have the function to create the plots, the X-Y data is pre-generated to create the plots. I hope I have stated the question clearly. if not, please do ask me again.
Thank you very much.

采纳的回答

Bernhard Suhm
Bernhard Suhm 2018-8-4
Have you tried using multcompare on the stats object that aoctool delivers, like alluded to in the doc page for aoctool ?

更多回答(0 个)

类别

Help CenterFile Exchange 中查找有关 Sequence and Numeric Feature Data Workflows 的更多信息

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by