Pith Number

pith:LKC2F5GK

pith:2026:LKC2F5GKVYE45LBZVRN4PUJXM6

not attested not anchored not stored refs resolved

A Fast Robust Adaptive filter using Improved Data-Reuse Method

Haiquan Zhao, Jinhui Hu, Yi Peng

The RTGA-IDROC algorithm merges total least squares with robust adaptation and improved data reuse to handle input noise while speeding early convergence.

arxiv:2605.18417 v1 · 2026-05-18 · eess.SP

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{LKC2F5GKVYE45LBZVRN4PUJXM6}

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 open · sign in to claim

4 Citations open

5 Replications open

✓ 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.

Claims

C1strongest claim

The proposed RTGA-IDROC algorithm not only effectively handles input noise under the errors-in-variables (EIV) model but also achieves excellent performance across diverse noise environments, with faster convergence enabled by the improved data reuse method without compromising steady-state performance.

C2weakest assumption

The local stability analysis and theoretical steady-state mean-square deviation derivation rest on modeling assumptions about the noise and input statistics that are typical in adaptive filtering but may not hold uniformly across the diverse real-world noise conditions claimed.

C3one line summary

Introduces RTGA-IDROC adaptive filter that integrates TLS and RGA advantages with IDR for speed and OC for efficiency, plus local stability analysis and MSD derivation, validated in simulations.

References

50 extracted · 50 resolved · 0 Pith anchors

[1] S. S. Haykin, Adaptive filter theory. Pearson Education India, 2002 2002

[2] Robust widely linear aﬀine projection m-estimate adaptive algorithm: Performance analysis and application, 2023

[3] Proportionate total adaptive filtering algorithms for sparse system identification, 2023

[4] Robust minimum disturbance diffusion lms for distributed estimation, 2020

[5] An augmented complex- valued gradient-descent total least-squares algorithm for noncir- cular signals, 2025

Formal links

1 machine-checked theorem link

Receipt and verification

First computed	2026-05-20T00:05:59.666338Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

5a85a2f4caae09ceac39ac5bc7d137678c4d0965430d2b151f94e4cbade800b4

Aliases

arxiv: 2605.18417 · arxiv_version: 2605.18417v1 · doi: 10.48550/arxiv.2605.18417 · pith_short_12: LKC2F5GKVYE4 · pith_short_16: LKC2F5GKVYE45LBZ · pith_short_8: LKC2F5GK

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/LKC2F5GKVYE45LBZVRN4PUJXM6 \
  | 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: 5a85a2f4caae09ceac39ac5bc7d137678c4d0965430d2b151f94e4cbade800b4

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "6e74a5a454e0b849fe017149a6ce3cdb1e8c5ddea8cd5f9e1b9b062fd6d77e7a",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "eess.SP",
    "submitted_at": "2026-05-18T13:52:57Z",
    "title_canon_sha256": "2d2fcc1bee9060710b61535e4baa73552aa99b2e9fb4be97cc190bbea35ebcf6"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.18417",
    "kind": "arxiv",
    "version": 1
  }
}