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A computationally efficient hybrid approach based on artificial neural networks and the wavelet transform for quantum simulations of graphene nanoribbon FETs
Research article (Journal of Computational Electronics, 2019) · cited 32× · AI/ML
A computationally efficient hybrid approach based on artificial neural networks and the wavelet transform for quantum simulations of graphene nanoribbon FETs
Summary
A computationally efficient hybrid approach based on artificial neural networks and the wavelet transform for quantum simulations of graphene nanoribbon FETs is a scholarly article[1].
Key Facts
A computationally efficient hybrid approach based on artificial neural networks and the wavelet transform for quantum simulations of graphene nanoribbon FETs's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). A computationally efficient hybrid approach based on artificial neural networks and the wavelet transform for quantum simulations of graphene nanoribbon FETs. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-computationally-efficient-hybrid-approach-based-on-artificial-neural-networks-and-the-wavelet-transform-for-quantum-si
MLA“A computationally efficient hybrid approach based on artificial neural networks and the wavelet transform for quantum simulations of graphene nanoribbon FETs.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-computationally-efficient-hybrid-approach-based-on-artificial-neural-networks-and-the-wavelet-transform-for-quantum-si.
BibTeX@misc{4ortxyz_a-computationally-efficient-hybrid-approach-based-on-artificial-neural-networks-and-the-wavelet-transform-for-quantum-si_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A computationally efficient hybrid approach based on artificial neural networks and the wavelet transform for quantum simulations of graphene nanoribbon FETs}}, year = {2026}, url = {https://4ort.xyz/entity/a-computationally-efficient-hybrid-approach-based-on-artificial-neural-networks-and-the-wavelet-transform-for-quantum-si}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A computationally efficient hybrid approach based on artificial neural networks and the wavelet transform for quantum simulations of graphene nanoribbon FETs — https://4ort.xyz/entity/a-computationally-efficient-hybrid-approach-based-on-artificial-neural-networks-and-the-wavelet-transform-for-quantum-si (retrieved 2026-05-24)
