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CNN Verilog Report en by ritwik ashok is a document available to read on EtoBox.

This research paper presents the design and implementation of a Convolutional Neural Network (CNN) using Verilog, aimed at enhancing neuromorphic technology for efficient data processing. The CNN is trained on the MNIST handwritten digit dataset, achieving an accuracy rate of 94% or higher, with the design verified through simulation and analysis. The study highlights the advantages of neuromorphic architecture over traditional Von Neumann systems, emphasizing its potential applications in various fields su

Author

ritwik ashok

Language

EN