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Paper Citation Record · LEDGER

Unobservable Systems: No Problem for Noise Identification

As of 8 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2505.23983.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.23983 v2

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:45:31.157316Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

28 of 28 outbound references displayed

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  • verified fuzzy21
  • unresolved7
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d06ed65d-1afe-47a9-85af-ab780168a937 · outbound

This paper cites Autonomous tracking and state estimation with generalized group lasso,.

Unobservable Systems: No Problem for Noise Identification Autonomous tracking and state estimation with generalized group lasso,

Reference 1

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Source-reported events for the cited work

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Observation 4fb1cf40-473d-4f8c-ba66-a5396090a1e0 · outbound

This paper cites Approaches to adaptive filtering,.

Unobservable Systems: No Problem for Noise Identification Approaches to adaptive filtering,

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 1b9d4361-2644-4733-99ff-e42d373c9e8d · outbound

This paper cites Noise covariance matrices in state-space models: A survey and comparison - part I,.

Unobservable Systems: No Problem for Noise Identification Noise covariance matrices in state-space models: A survey and comparison - part I,

Reference 3

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Source-reported events for the cited work

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Observation fe03633a-233d-4b06-92a0-7265b881981d · outbound

This paper cites Recursive noise adaptive Kalman filtering by variational Bayesian approximations,.

Unobservable Systems: No Problem for Noise Identification Recursive noise adaptive Kalman filtering by variational Bayesian approximations,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation ec46e1c4-1b0c-458d-ab67-6f7fc05b3119 · outbound

This paper cites Variational adaptive Kalman filter with Gaussian-Inverse-Wishart mixture distribution,.

Unobservable Systems: No Problem for Noise Identification Variational adaptive Kalman filter with Gaussian-Inverse-Wishart mixture distribution,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 9bfa8b52-e479-400e-aa88-f3b681e3cdc0 · outbound

This paper cites an unresolved cited work.

Unobservable Systems: No Problem for Noise Identification Unresolved cited work

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e0f783d9-31ec-4e1e-ab26-78ad9ed43ea4 · outbound

This paper cites Esti- mating model error covariance matrix parameters in extended Kalman filtering,.

Unobservable Systems: No Problem for Noise Identification Esti- mating model error covariance matrix parameters in extended Kalman filtering,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 86681748-a6f5-4379-9f46-64012a594935 · outbound

This paper cites an unresolved cited work.

Unobservable Systems: No Problem for Noise Identification Unresolved cited work

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation ff57d703-9413-4499-ab9b-296e221f0fe7 · outbound

This paper cites System identification of nonlinear state-space models,.

Unobservable Systems: No Problem for Noise Identification System identification of nonlinear state-space models,

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6548a615-8a8d-453e-93e5-2a33b38f0195 · outbound

This paper cites Model error estimation using the expectation maximization algorithm and a particle flow filter,.

Unobservable Systems: No Problem for Noise Identification Model error estimation using the expectation maximization algorithm and a particle flow filter,

Reference 10

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 967d8763-019a-4264-8442-48709b64bcc3 · outbound

This paper cites Adaptive Kalman-Informed Transformer.

Unobservable Systems: No Problem for Noise Identification Adaptive Kalman-Informed Transformer

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation aae6d56f-cebe-4a2d-a0a6-bfa09d5942a0 · outbound

This paper cites Estimation of noise covariance matrices for a linear time-varying stochastic process,.

Unobservable Systems: No Problem for Noise Identification Estimation of noise covariance matrices for a linear time-varying stochastic process,

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation b46b8bec-9308-486f-9bcb-f07be6305a5e · outbound

This paper cites A new autocovari- ance least-squares method for estimating noise covariances,.

Unobservable Systems: No Problem for Noise Identification A new autocovari- ance least-squares method for estimating noise covariances,

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 519d6ff6-9e11-4a16-81d6-6b36618c36cc · outbound

This paper cites Measurement difference method: A universal tool for noise identification,.

Unobservable Systems: No Problem for Noise Identification Measurement difference method: A universal tool for noise identification,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 560306df-b70b-4706-bd67-dbb4e5c04796 · outbound

This paper cites A tutorial on the two-state model of the atomic clock noise,.

Unobservable Systems: No Problem for Noise Identification A tutorial on the two-state model of the atomic clock noise,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation de8ad98e-b833-42a6-828f-291f08a5f19a · outbound

This paper cites Time and the Kalman Filter: Applications of optimal estimation to atomic timing,.

Unobservable Systems: No Problem for Noise Identification Time and the Kalman Filter: Applications of optimal estimation to atomic timing,

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 49b3d866-2c11-48dc-afec-18aa37bf7c4f · outbound

This paper cites Bar-Shalom, X.

Unobservable Systems: No Problem for Noise Identification Bar-Shalom, X

Reference 17

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e6d0fcd1-5f96-4a79-8512-a384fb3c4d11 · outbound

This paper cites A fast distributed variational Bayesian filtering for multisensor ltv system with non-Gaussian noise,.

Unobservable Systems: No Problem for Noise Identification A fast distributed variational Bayesian filtering for multisensor ltv system with non-Gaussian noise,

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e61ae7c7-72ec-4989-93f8-985775ef4ee5 · outbound

This paper cites Design of measurement difference autocovariance method for estimation of process and measurement noise covariances,.

Unobservable Systems: No Problem for Noise Identification Design of measurement difference autocovariance method for estimation of process and measurement noise covariances,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation a360593c-5e7e-401e-9c55-e96afd9443d5 · outbound

This paper cites Noise covariances identification by MDM: Weighting, recursion, and implementation,.

Unobservable Systems: No Problem for Noise Identification Noise covariances identification by MDM: Weighting, recursion, and implementation,

Reference 20

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation fcdc8735-7c76-45c1-b115-4644a912e1e5 · outbound

This paper cites an unresolved cited work.

Unobservable Systems: No Problem for Noise Identification Unresolved cited work

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 57ee644f-672f-4e17-9fc1-980a94c9d7ad · outbound

This paper cites an unresolved cited work.

Unobservable Systems: No Problem for Noise Identification Unresolved cited work

Reference 22

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unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4d652b2a-8e55-429a-9446-92b7ca36c9e8 · outbound

This paper cites Identifiability analysis of noise covariances for LTI stochastic systems with unknown inputs,.

Unobservable Systems: No Problem for Noise Identification Identifiability analysis of noise covariances for LTI stochastic systems with unknown inputs,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4668d73a-5b7b-4d4a-a2d2-f1776b1085ec · outbound

This paper cites Identifiability of unique elements of noise covariances in state-space models,.

Unobservable Systems: No Problem for Noise Identification Identifiability of unique elements of noise covariances in state-space models,

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation ec4d2394-3eb4-413d-a5ec-d2fc5465ec18 · outbound

This paper cites Covariance estimation and gaussianity assessment for state and measurement noise,.

Unobservable Systems: No Problem for Noise Identification Covariance estimation and gaussianity assessment for state and measurement noise,

Reference 25

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 62791a71-f723-46ce-ac1e-2ea91b311bc3 · outbound

This paper cites Correlated noise characteristics estimation for linear time-varying systems,.

Unobservable Systems: No Problem for Noise Identification Correlated noise characteristics estimation for linear time-varying systems,

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-07T12:45:31.718037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 5aabb806-f13c-48ba-baf5-43c52f2d127d · outbound

This paper cites Noise moment and parameter estimation of state-space model,.

Unobservable Systems: No Problem for Noise Identification Noise moment and parameter estimation of state-space model,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:31.548028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4b1cc16c-547e-44eb-a9bb-2ea428f29675 · outbound

This paper cites Identification of GNSS measurement error: From time to elevation dependency,.

Unobservable Systems: No Problem for Noise Identification Identification of GNSS measurement error: From time to elevation dependency,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:45:31.362992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Pith citing papers

No inbound Pith citation observations are available.