Convolutional codes represent a cornerstone in modern communications, offering a method for continuously encoding data streams to mitigate errors due to interference and noise. These codes operate by ...
Abstract: This paper introduces a convolutional syndrome former (CSF) which enables reduced complexity decoding of regularly punctured convolutional codes (CCs) of rate r/(r + 1). The CSF is derived ...
Introduction: In the field of brain-computer interfaces (BCI), motor imagery (MI) classification is a critically important task, with the primary objective of decoding an individual's MI intentions ...
ABSTRACT: A new nano-based architectural design of multiple-stream convolutional homeomorphic error-control coding will be conducted, and a corresponding hierarchical implementation of important class ...
Motor imagery (MI) electroencephalogram (EEG) decoding plays a critical role in brain–computer interfaces but remains challenging due to large inter-subject variability and limited training data.
This paper describes an ASIP decoder template suitable for multi-standard Viterbi, Turbo and LDPC decoding. We show architecture fitness for WLAN, WiMAX and 3GPPLTE standards, although various other ...
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