Pith Number
pith:JZUWWPUC
pith:2013:JZUWWPUCGSOYPVJMF5B2HNW4LG
not attested
not anchored
not stored
refs pending
Impulsive Noise Mitigation in Powerline Communications Using Sparse Bayesian Learning
arxiv:1303.1217 v1 · 2013-03-05 · stat.ML · cs.IT · math.IT
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{JZUWWPUCGSOYPVJMF5B2HNW4LG}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
1
Bitcoin timestamp
2
Internet Archive
3
Author claim
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claim
4
Citations
5
Replications
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Portable graph bundle live · download bundle · merged
state
The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same
current state with the deterministic merge algorithm.
Receipt and verification
| First computed | 2026-05-18T00:57:56.518844Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
4e696b3e82349d87d52c2f43a3b6dc59807c035e908d00a972cb05f639c9d83c
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/JZUWWPUCGSOYPVJMF5B2HNW4LG \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 4e696b3e82349d87d52c2f43a3b6dc59807c035e908d00a972cb05f639c9d83c
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "3f850889a6117a0c0725c7cabef5d77c7b2113ef3770d73b6aec76303d09d856",
"cross_cats_sorted": [
"cs.IT",
"math.IT"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "stat.ML",
"submitted_at": "2013-03-05T22:58:24Z",
"title_canon_sha256": "a8ab620840c0ba9790646dabd84c2f07a18bde3974559c2799ced6415f9df766"
},
"schema_version": "1.0",
"source": {
"id": "1303.1217",
"kind": "arxiv",
"version": 1
}
}