Artificial Intelligence and Quantum Computing for Advanced Wireless Networks. Savo G. Glisic

Artificial Intelligence and Quantum Computing for Advanced Wireless Networks - Savo G. Glisic


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Spaces and Fixed Point Theory. New York: Wiley.

      63 63 Powell, M.J.D. (1964). An efficient method for finding the minimum of a function of several variables without calculating derivatives. Comput. J. 7: 155–162.

      64 64 Frasconi, P., Gori, M., and Sperduti, A. (1998). A general framework for adaptive processing of data structures. IEEE Trans. Neural Netw. 9 (5): 768–786.

      65 65 L. Almeida, “A learning rule for asynchronous perceptrons with feedback in a combinatorial environment,” in Proc. IEEE Int. Conf. Neural Netw., M. Caudill and C. Butler, Eds., San Diego, 1987, vol. 2, pp. 609–618.

      66 66 Pineda, F. (1987). Generalization of back‐propagation to recurrent neural networks. Phys. Rev. Lett. 59: 2229–2232.

      67 67 Graham, A. (1982). Kronecker Products and Matrix Calculus: With Applications. New York: Wiley.

      68 68 R. Singh, A. Chakraborty and B. S. Manoj, Graph Fourier Transform based on Directed Laplacian, https://arxiv.org/pdf/1601.03204.pdf

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