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The average time of our algorithm was 97 ms per frame, while the average calculation time of the contrast algorithm was 151 ms per frame.
It corresponds to a processing time of 200 ms per frame.
The MC MDT spends time in evaluating CGs, but its decoding time is reduced by 4 ms per frame.
This result in approximately 24.6 ms per frame processing time, which is smaller than the speech signal frame rate.
However, the hierarchical depth estimation requires approximately 190 ms per frame, which is an order of magnitude slower than our FPGA implementation.
At 5 ms per frame, this corresponds to 0.25 second of real time (or about 2.5 coherence times of the channel, at 10 Hz Doppler).
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Table 5 Performance comparison between SIS-based tracking and the proposed method Method Number of particles Processing time for sampling (ms) Average time per frame (ms) Frame processing rate (fps) Tracking failures SIS-based tracking 250 23.55 96.56 10.36 31 SIS-based tracking 1000 114.33 187.34 5.34 22 Proposed method 250 25004 96.06 10.41 9.
Because PIP2 binding occurs on the microsecond time scale (see above), it was too fast to detect (20 ms per TIRF frame).
Parameter Value MAC layer Channel capacity 32 Mbps QPSK) Number of subchannels 30 Symbol rate 16 Megabaud Slot size 1 byte Frame duration 4 ms Physical slots per frame 4000 Downlink/uplink ratio Ranging opps.
Usually sequences of 2.5 min time lapse were recorded with 1 frame taken every 5 s and 500 ms exposure time per frame.
We computed this by estimating the position (x, y, z) every 1 ms (10 estimations per frame) and by adding the convolved PSF at (x, y, z) to the final image.
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