Abstract
A supervised Artificial Neural Network (ANN) based system is being developed employing the Bi-polar function for identifying stellar images in CCD frames. It is based on feed-forward artificial neural networks with error back-propagation learning. It has been coded in C language. The learning process was performed on a 341 input pattern set, while a similar set was used for testing. The present approach has been applied on a CCD frame of the open star cluster M67. The results obtained have been discussed and compared with those derived in our previous work employing the Uni-polar function and by a package known in the astronomical community (DAOPHOT-II). Full agreement was found between the present approach, that of Elnagahy et al, and the standard astronomical data for the cluster. It has been shown that the developed technique resembles that of the Uni-Polar function, possessing a simple, much faster yet reliable approach. Moreover, neither prior knowledge on, nor initial data from, the frame to be analysed is required, as it is for DAOPHOT-II.
Highlights
Is stellar astronomy the oldest topic in astronomical studies, but it continues to be of importance in astronomical research
The selected case frame was reduced by applying the present Artificial Neural Network based System (ANNS) approach as well as that of Paper I and the DAOPHOT-II code
The computing time is similar to that needed for Paper I, i.e., 45 seconds employing a Pentium II PC (233 MHz Processor) for scanning the image, finding the data limits of the pixels, displaying the frame via the monitor, recognising stellar images and cosmic events and saving the output in the relevant files
Summary
Is stellar astronomy the oldest topic in astronomical studies, but it continues to be of importance in astronomical research. The codes based on these models, usually a bi-variant Gaussian function, require a user-computer interface facility for providing the form of the model adopted and for setting the initial values of the model parameters. Several runs of such codes are necessary to optimise and derive the final set of parameters, through some non-linear fitting process, to be applicable for CCD frame reduction. Such circumstances require a fast computing machine provided with a large memory and working space area as well as an expert user. A bipolar function has been adopted and applied on the same frame, and the outcome has been investigated and compared with the previous ones
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