NEAILGJul 6, 2021

Neural Computing

arXiv:2107.02744v139 citations
Originality Synthesis-oriented
AI Analysis

It provides an educational overview for domain-specific audiences, but is incremental as it summarizes prior work without new results.

This chapter reviews existing neural network types and their applications to societal problems, aiming to inspire innovation among educators and researchers.

This chapter aims to provide next-level understanding of the problems of the world and the solutions available to those problems, which lie very well within the domain of neural computing, and at the same time are intelligent in their approach, to invoke a sense of innovation among the educationalists, researchers, academic professionals, students and people concerned, by highlighting the work done by major researchers and innovators in this field and thus, encouraging the readers to develop newer and more advanced techniques for the same. By means of this chapter, the societal problems are discussed and various solutions are also given by means of the theories presented and researches done so far. Different types of neural networks discovered so far and applications of some of those neural networks are focused on, apart from their theoretical understanding, the working and core concepts involved in the applications.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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