1. Yang, T.-J., Chen, Y.-H., Emer, J., Sze, V.: A method to estimate the energy consumption of deep neural networks. In: 2017 51st Asilomar Conference on Signals, Systems, and Computers, pp. 1916–1920. IEEE, Piscataway (2017)
2. “PrimePower” https://www.synopsys.com/implementation-and-signoff/signoff/primepower.html
3. Nourani, M., Nazarian, S., Afzali-Kusha, A.: A parallel algorithm for power estimation at gate level. In: MWSCAS, pp. I–511 (2002)
4. Mehta, H., Borah, M., Owens, R.M., Irwin, M.J.: Accurate estimation of combinational circuit activity. In: Proceedings of the 32nd annual ACM/IEEE Design Automation Conference (DAC ’95)
5. Najm, F.N.: Transition density: a new measure of activity in digital circuits. IEEE Trans. Comput. Aided Desig. Integr. Circuits Syst. 12(2), 310–323 (1993). https://doi.org/10.1109/43.205010