Abstract
Neural networks are the mathematical models that process information or any signal based on biological neuron. The structure of these networks is very complex as it consists of interconnected neurons that make problem-solving less complicated. Since artificial neural networks (ANN) can be used in various applications specifically in the field of computer science and electronics; the researchers are designing artificial neural networks to find solutions to problems like recognition of pattern, optimization, prediction, associative memory, and control. This chapter gives the basic knowledge of artificial neural networks, its general architecture, and various categories. The chapter focuses on different models, their mathematical proof, and applications in real life. It also covers the detailed information about the use of ANN in different sectors.
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Katal, A., Singh, N. (2022). Artificial Neural Network: Models, Applications, and Challenges. In: Tomar, R., Hina, M.D., Zitouni, R., Ramdane-Cherif, A. (eds) Innovative Trends in Computational Intelligence. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-78284-9_11
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