Pith Number
pith:WMY5IIWD
pith:2018:WMY5IIWDUDA6MQNG4ZY3SI34NA
not attested
not anchored
not stored
refs pending
Channel Tracking for Wireless Energy Transfer: A Deep Recurrent Neural Network Approach
arxiv:1812.02986 v1 · 2018-12-07 · cs.IT · math.IT
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{WMY5IIWDUDA6MQNG4ZY3SI34NA}
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 | 2026-05-17T23:58:51.201519Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
b331d422c3a0c1e641a6e671b9237c680c681a981d01e7347361335597d37553
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/WMY5IIWDUDA6MQNG4ZY3SI34NA \
| 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: b331d422c3a0c1e641a6e671b9237c680c681a981d01e7347361335597d37553
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "e0eadae97e41e138a780609d76207d7543f88d709bd5f0a050ec37b69c1a112e",
"cross_cats_sorted": [
"math.IT"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.IT",
"submitted_at": "2018-12-07T11:32:08Z",
"title_canon_sha256": "8da58427d508830c6bb91a14e649dad216f0d6d41b1f2cdf98a5911d1be1068a"
},
"schema_version": "1.0",
"source": {
"id": "1812.02986",
"kind": "arxiv",
"version": 1
}
}