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Reverse Engineering’s Neural Network Approach to the Human Brain
Abstract
The organic components of the brain are capable of performing consistently and successfully in noisy situations. Brain components with highly adaptive or flexible interactions that could be low-precision, unpredictable, or excessively simultaneous are used to construct biological circuits. Two of the most remarkable characteristics of brain networks are their propensity to self-organize and their pattern organization. Recent research on neural networks, including artificial neural networks and convolutional neural networks (CNN), has uncovered some fascinating concepts. The only way to comprehend these concepts and use them to solve actual issues is through the construction of largescale, sophisticated brain simulations. With the most recent improvements to low-cost multiprocessor computers, large-scale network simulations are now feasible. Conceptual paradigms of NN methods for designing, generating, and evaluating advanced neural systems are discussed in this study.
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References
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DOI: https://doi.org/10.37591/joces.v12i2.951
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