Proofs for the Four Fundamental Equations of the Backpropagation and Algorithms in Feedforward Neural Networks

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This paper will focus on proving the four fundamental equations of the backpropagation. Then I will show how to use this algorithm combined with the stochastic gradient descent technique to implement the network for recognizing the handwritten digits. Parts of the proof are provided by the author Michael Nielsen in his online book Neural Networks and Deep Learning. Meanwhile, this paper will provide more details of his proofs and some basic definitions of gradient.

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APA

Li, H. (2022). Proofs for the Four Fundamental Equations of the Backpropagation and Algorithms in Feedforward Neural Networks. Afribary. Retrieved from https://afribary.com/works/paper-2123

MLA 8th

Li, Hao "Proofs for the Four Fundamental Equations of the Backpropagation and Algorithms in Feedforward Neural Networks" Afribary. Afribary, 24 Apr. 2022, https://afribary.com/works/paper-2123. Accessed 25 May. 2022.

MLA7

Li, Hao . "Proofs for the Four Fundamental Equations of the Backpropagation and Algorithms in Feedforward Neural Networks". Afribary, Afribary, 24 Apr. 2022. Web. 25 May. 2022. < https://afribary.com/works/paper-2123 >.

Chicago

Li, Hao . "Proofs for the Four Fundamental Equations of the Backpropagation and Algorithms in Feedforward Neural Networks" Afribary (2022). Accessed May 25, 2022. https://afribary.com/works/paper-2123