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. Author manuscript; available in PMC: 2024 Oct 5.
Published in final edited form as: IEEE Trans Neural Netw Learn Syst. 2023 Oct 5;34(10):6983–7003. doi: 10.1109/TNNLS.2022.3145365

Fig. 1.

Fig. 1.

Computational graph of RNN. o is the RNN output, and L presents the difference between the RNN output and the desired output (target or label). L is commonly used for calculating the loss function.