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Paper Citation Record · LEDGER

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set

As of 13 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2412.03936.

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

pith.paper-citation-record.v1
2412.03936 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:59:28.686869Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

17 of 17 outbound references displayed

  • verified exact1
  • verified fuzzy9
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bc9c9835-190c-4a73-a847-5b367ee6c3a9 · outbound

This paper cites Modeling radio-frequency devices based on deep learning technique.

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set Modeling radio-frequency devices based on deep learning technique

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-11T21:59:28.854365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 8d7d7090-15c8-48b0-8b3e-e0bd95568e5a · outbound

This paper cites an unresolved cited work.

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set Unresolved cited work

Reference 2

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raw_fallback, observed 2026-08-11T21:59:28.845344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation f87dd573-4fbd-47a8-b8f6-959bd93e0596 · outbound

This paper cites an unresolved cited work.

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set Unresolved cited work

Reference 3

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raw_fallback, observed 2026-08-11T21:59:28.836321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 007361dc-f461-4f59-a4b5-e8c482a81b29 · outbound

This paper cites Neural-based dynamic modeling of nonlinear microwave circuits.

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set Neural-based dynamic modeling of nonlinear microwave circuits

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-11T21:59:28.827206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T21:59:28.642463Z digest=sha256:46c266da8a5534c353e1b9ea69ee2422a811523b65cbd81a52b1011b9969b3f0

Observation 4628b374-f65f-4d5c-989b-28b7163e358f · outbound

This paper cites WaveNet: A Generative Model for Raw Audio.

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set WaveNet: A Generative Model for Raw Audio

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e752e437-3ba2-4a61-9c38-4c5d2ec62b9d · outbound

This paper cites Very deep convolutional neural networks for raw waveforms.

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set Very deep convolutional neural networks for raw waveforms

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-11T21:59:28.817611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T21:59:28.650184Z digest=sha256:a6983ef40a0293854e3c36c2322fb363a3aabfe3a90e351d7ba755b0ef2c2d5c

Observation c81b5139-337c-4968-9c42-a68c04aee4ef · outbound

This paper cites iTransformer: Inverted Transformers Are Effective for Time Series Forecasting.

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set iTransformer: Inverted Transformers Are Effective for Time Series Forecasting

Reference 7

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unresolved
no resolver link, observed 2026-08-11T21:59:28.654166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:59:28.654166Z digest=sha256:689684485f99b02682246b5f44044b078ca9e2cff8b0e77ddaf7afd0ad2378a2

Observation dfe9ce7e-0dbf-4203-b985-31179f68ee82 · outbound

This paper cites Dynamic behavioral modeling of 3g power amplifiers using real-valued time-delay neural networks.

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set Dynamic behavioral modeling of 3g power amplifiers using real-valued time-delay neural networks

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-11T21:59:28.808544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T21:59:28.658097Z digest=sha256:46a3ee39510d4b5e8ab0cc07587f5f51641356fb5571cdc59ca6f09de32f4353

Observation 04d0d2b8-d53b-4576-acbf-7a9f28377076 · outbound

This paper cites High-speed nonlinear circuit macromod- eling using hybrid-module clockwork recurrent neural network.

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set High-speed nonlinear circuit macromod- eling using hybrid-module clockwork recurrent neural network

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-11T21:59:28.798656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T21:59:28.661737Z digest=sha256:e152938d6a3a7e15fc8a275dfeeb9f9c140766802ba3af3fb46dff92c1790fbf

Observation 9e1ea97e-e6b9-4792-8b0b-2b9d15ffb62c · outbound

This paper cites Fast Transient Simulation of High-Speed Channels Using Recurrent Neural Network.

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set Fast Transient Simulation of High-Speed Channels Using Recurrent Neural Network

Reference 10

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verified exact
local_arxiv, observed 2026-08-11T21:59:28.730125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T21:59:28.665122Z digest=sha256:265c67e861e358de173a66ab5a25f24b5f86edb1e2d57e129caf5b5a90d67a77

Observation daed0502-43a8-4d92-b295-91720cae8222 · outbound

This paper cites Deep stacked autoencoder- based long-term spectrum prediction using real-world data.

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set Deep stacked autoencoder- based long-term spectrum prediction using real-world data

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-11T21:59:28.789142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T21:59:28.668443Z digest=sha256:0da7711c9aeb1f06914738a164616af9d992a295a544cfd4c1e1ad8ab9d78c2a

Observation 9b8577e6-ecb8-430e-8057-4c5eee979640 · outbound

This paper cites A decoder-only foundation model for time-series forecasting.

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set A decoder-only foundation model for time-series forecasting

Reference 12

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no resolver link, observed 2026-08-11T21:59:28.671705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:59:28.671705Z digest=sha256:166f9ac6a8dc03d76ab8479660b0cd3403d0f8908916c3b4e70423b7b809e970

Observation b569aaf3-4636-45a3-b046-73e95d33e2cc · outbound

This paper cites Analysis of machine learning techniques for time domain waveform prediction in analog and mixed signal integrated circuit verification.

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set Analysis of machine learning techniques for time domain waveform prediction in analog and mixed signal integrated circuit verification

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:59:28.779496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T21:59:28.674978Z digest=sha256:31ec86cc5539482df7eb60dc18753559319c1c9ede8ade58dc46d1d8bc0b5af9

Observation b17e03cb-f6a3-401b-bd14-f9eb0e221f57 · outbound

This paper cites Macromodeling of nonlinear high- speed circuits using novel hybrid bidirectional high-order deep recurrent neural network.

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set Macromodeling of nonlinear high- speed circuits using novel hybrid bidirectional high-order deep recurrent neural network

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:59:28.769675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T21:59:28.677911Z digest=sha256:6cdc42f87cf6d51d5249571d31aa52361b534a5700e1d8b7daf52d8d43975913

Observation 694fddbf-1166-4785-a173-c71c47d285b8 · outbound

This paper cites Batch- normalized deep recurrent neural network for high-speed nonlinear circuit macromodeling.

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set Batch- normalized deep recurrent neural network for high-speed nonlinear circuit macromodeling

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-11T21:59:28.760239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T21:59:28.680725Z digest=sha256:3cdf6b8ee5e9825fb4b5bc75ec3b112e053aeed440736c07496ee20a2409e69e

Observation 1285e630-0306-4790-a4e0-d89be02f6174 · outbound

This paper cites Deep residual learning for image recognition.

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set Deep residual learning for image recognition

Reference 16

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unresolved
no resolver link, observed 2026-08-11T21:59:28.683668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:59:28.683668Z digest=sha256:a5dfc4ec07d5fb8e447631e3fedd6b14620c6d71f12d377c8215bc753859fb06

Observation 9e1fd5e4-5368-4cb4-892a-7fe11558b3eb · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 17

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no resolver link, observed 2026-08-11T21:59:28.686869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.