Low-Complexity Vector-by-Vector Detector for AFDM-IM Systems by Reconstructing Sparse Channel Matrix
Abstract: In this letter, a low-complexity vector-by-vector aided expectation propagation (VV-EP) detector is proposed for affine frequency division multiplexing (AFDM) with index modulation (IM) ...
Abstract: Deep Neural Networks (DNN) have realized significant achievements across various application domains. There is no doubt that testing and enhancing a pre-trained DNN that has been deployed in ...
Vector Post-Training Quantization (VPTQ) is a novel Post-Training Quantization method that leverages Vector Quantization to high accuracy on LLMs at an extremely low bit-width (<2-bit). VPTQ can ...
Deep Learning-based embeddings are used widely for “dense retrieval” in information retrieval, computer vision, NLP, amongst others, owing to capture diverse types of semantic information. This ...
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