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The decoder performs the reverse process.
Assume packet containing video data is lost in the channel and the decoder performs error concealment.
The decoder performs a motion search based on the hash to generate the best SI block from the previous frame.
Additionally, the decoder performs a carrier-to-interference and noise ratio (CINR) estimation based on the demodulated data symbols by computing an error vector magnitude (EVM) measurement.
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First, the decoder performed very well on forced choices, with nearly all decoder errors lying just on the wrong side of the threshold and not strongly favoring the opposite choice.
By letting the decoder adapt more, we can see during trials 200 300 the performance could reach to the level that was before reorganization where the decoder performed the task perfectly.
At the final time point (200 ms before movement onset), the decoder performed correctly on 99% of forced-choice trials for monkey J and 94% of trials for monkey N (p < 10−6 for each dataset assessed individually, 'Materials and methods').
Indeed, although this decoder performs worst in quiet, it proves more robust than the hemispheric decoder.
Based on the recursive structure of the polar encoder, the SC decoder performs a series of interlaced step-by-step decisions in which a decision in each step heavily depends on the decisions in the previous steps and the received sequence (y_{1}^{N}) from channel.
Second, the hemispheric decoder performs worse than the two other decoders above 700 Hz for the guinea pig models and above 500 Hz for the cat.
The hemispheric decoder performs better than both decoders for the guinea pig model at all frequencies, but for the cat, it is only better than the smoothed peak decoder for frequencies below 600 Hz.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com