Understanding whether cognitive and perceptual states can be decoded from brain activity alone is a fundamental question in cognitive neuroscience. It is not only relevant for scientific theories of ...
Neural decoding is the study of what information is available in the electrical activity (action potentials) of individual cells or networks of neurons. Studies of neural decoding aim to identify what ...
Abstract: Decoding neural signals of silent reading with Brain-Computer Interface (BCI) techniques presents a fast and intuitive communication method for severely aphasia patients.
Abstract: Polar codes are high density parity check codes and hence the sparse factor graph, instead of the parity check matrix, has been used to practically represent an LP polytope for LP decoding.
Python implementation of some common Connectionist Temporal Classification (CTC) decoding algorithms. A minimalistic language model is provided. The output mat (numpy array, softmax already applied) ...
The package contains a mixture of classic decoding methods and modern machine learning methods. For regression, we currently include: Wiener Filter, Wiener Cascade, Kalman Filter, Naive Bayes, Support ...
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