CATS-Net (Concept Abstraction and Task-Solving Network) is a comprehensive framework for understanding and implementing concept abstraction in neural networks. The system combines supervised learning ...
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Abstract: This article proposes a neural network (NN)-based calibration framework via quantization code reconstruction to address the critical limitation of multidimensional NNs (MDNNs) in ...
Abstract: Ordered statistics decoding has been instrumental in addressing decoding failures that persist after normalized min-sum decoding in short low-density parity-check codes. Despite its benefits ...
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