Emulation of the Global (sky-averaged) 21-cm signal from the Cosmic Dawn and Epoch of Reionization with neural networks has been shown to be an essential tool for physical signal modelling. In this paper we present globalemu, a Global 21-cm signal emulator that uses redshift as a character defining variable along side a set of astrophysical parameters to estimate the brightness temperature of the 21-cm signal. Combined with a physically motivated pre-processing of the data this makes for a reliable and fast emulator that is relatively insensitive to the neural network design. A single high resolution signal can be emulated in 1.3 ms when using globalemu in comparison to 133 ms, a factor of 102 improvement, when using the existing public state of the art emulator 21cmGEM evaluated with the same computing power. We illustrate, with the same training and test data used for 21cmGEM, that globalemu is almost twice as accurate as 21cmGEM and for 95% of models in a test set of $approx1,700$ we can achieve a RMSE of $leq 5.37$ mK and a mean RMSE of 2.52 mK across the band z = 7 -28 (approximately 10% the expected noise of 25 mK for the Radio Experiment for the Analysis of Cosmic Hydrogen (REACH)). Further, globalemu provides a flexible framework in which the neutral fraction history and Global signal models with updated astrophysics can be emulated easily. The emulator is pip installable and available at: https://github.com/htjb/globalemu. globalemu will be used by the REACH collaboration to perform physical signal modelling inside a Bayesian nested sampling loop.
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