Enhanced fault detection in digital VLSI circuits using convolutional autoencoders

As Very Large-Scale Integration (VLSI) technology advances, the demand for reliable and scalable pre-silicon fault detection (FD) techniques continues to grow. Conventional diagnostic methods often face limitations in identifying subtle stuck-at faults within complex and high-dimensional test data....

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Vydané v:	Integration (Amsterdam) Ročník 107; s. 102608
Hlavní autori:	Savalam, Chandrasekhar, Medisetti, Sanjay, Korapati, Prasanti
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.03.2026
Predmet:	Contractive autoencoder Convolutional autoencoder Deep learning Digital VLSI circuits Error debugging Stacked sparse autoencoders Variational autoencoder Deep learning Contractive autoencoder Error debugging Stacked sparse autoencoders Variational autoencoder Convolutional autoencoder Digital VLSI circuits
ISSN:	0167-9260
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