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The redshifted 21-cm signal of neutral Hydrogen is a promising probe into theperiod of evolution of our Universe when the first stars were formed (CosmicDawn), to the period where the entire Universe changed its state from beingcompletely neutral to completely ionized (Reionization). The most strikingfeature of this line of neutral Hydrogen is that it can be observed across anentire frequency range as a sky-averaged continuous signature, or itsfluctuations can be measured using an interferometer. However, the 21-cm signalis very faint and is dominated by a much brighter Galactic and extra-galacticforegrounds, making it an observational challenge. We have used differentphysical models to simulate various realizations of the 21-cm Global signals,including an excess radio background to match the amplitude of the EDGES 21-cmsignal. First, we have used an artificial neural network (ANN) to extract theastrophysical parameters from these simulated datasets. Then, mock observationswere generated by adding a physically motivated foreground model and an ANN wasused to extract the astrophysical parameters from such data. The $R^2$ score ofour predictions from the mock-observations is in the range of 0.65-0.89. Wehave used this ANN to predict the signal parameters giving the EDGES data asthe input. We find that the reconstructed signal closely mimics the amplitudeof the reported detection. The recovered parameters can be used to infer thephysical state of the gas at high redshifts.

Using Artificial Neural Networks to extract the 21-cm Global Signal from the EDGES data