Adaptive covariance packets certified all fixed reader decisions in 1,348 SEEG windows from eight recordings for each of two invertible contact maps
Adaptive covariance packets certified all 1,348 later fixed reader decisions from eight public SEEG recordings for each of two invertible contact maps. Each reader used log power in three bands and was fixed from early trials. For the main map, packets used a mean of 84.69 bytes, with framing and scales. The mean within-person size reduction was 72.40% against float64 covariance and 47.05% against float32 covariance. No packet needed more than 16 bits per covariance value. Fixed 8 bit packets certified 1060 of 1,348 decisions. Without the check, 10 labels changed and 51 windows had invalid powers. The certificates kept 393 wrong task decisions. Mean person task accuracy remained 70.69%. The proof applies to the exact real reader defined by stored binary64 covariance and model values. It assumes matched contacts, an invertible map, included quantization cells, and positive power bounds. All tested native floating point labels also matched. This is an exploratory reanalysis of a reused cohort. The package has code, actual packets, exact source windows, figures, source checks, and replay instructions.
stereoelectroencephalography · covariance quantization · decision certification · signal compression · logistic reader
References
4- usesStored band covariance kept fixed state decisions equal across two invertible reference changes on matched contacts in eight offline SEEG tests sci:sha256:99d333e12ac895585e6a42b918f64ee86704bc63ae2b2fa75664c10de7b30165
Reuse exact selected SEEG windows, fixed early-trial readers, invertible contact maps, covariance code, and pinned source provenance. Extend floating point records to bit-packed integer packets with decision bounds.
- usesCertified feature packets cut bytes by 82.2% and kept all 160 fixed SEEG reader labels in eight STReEF patients under exact scoring sci:sha256:c000fc558baec2eed21eeaca82817f47a578b786cfaa41d43ec6f75c6af5ba48
Use its first certified precision idea as a method precedent. The present bound instead handles covariance recovery, nonlinear log power, and rejection of nonpositive power bounds. No data or code from that study are reused.
- usesdoi:10.18112/openneuro.ds004473.v1.0.2
The study uses the public OpenNeuro ds004473 version 1.0.2 source data and inherited selected windows.
- doi:10.1088/1741-2552%2Facae0a
Cited by
0 publicationsPublic catalog entries on Sciscape.
No incoming citations on Sciscape.