Matlab codes to implement the DeepVQCS method proposed in "Low-Complexity Vector Quantized Compressed Sensing via Deep Neural Networks" (M. Leinonen and M. Codreanu)

Matlab codes to implement the DeepVQCS method proposed in "Low-Complexity Vector Quantized Compressed Sensing via Deep Neural Networks" (M. Leinonen and M. Codreanu)

Beskrivning

Matlab codes to realize the DeepVQCS architecture and its training proposed in the journal paper by M. Leinonen and M. Codreanu, "Low-Complexity Vector Quantized Compressed Sensing via Deep Neural Networks", IEEE Open Journal of the Communications Society, Vol. 1, pp. 1278 - 1294, Aug. 2020. DOI: 10.1109/OJCOMS.2020.3020131
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Publiceringsår

2021

Upphovspersoner

CWC - Radioteknologiat - Utgivare

Markus Leinonen Orcid -palvelun logo - Upphovsperson

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Vetenskapsområden

El-, automations- och telekommunikationsteknik, elektronik

Språk

engelska

Öppen tillgång

Öppet

Licens

Creative Commons Attribution 4.0 International (CC BY 4.0)

Nyckelord

Machine learning, Compressed sensing, data compression, deep neural network, supervised learning, vector quantization