Paper Citation Record · LEDGER

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

As of 15 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 2026-08-15T06:32:42.880941+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

Resolution: 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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: unresolved; 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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: unresolved; 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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: 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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-11T21:59:28.646021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-15T06:32:42.880941+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: 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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: 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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: 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 2026-08-15T06:32:42.880941+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: 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 2026-08-15T06:32:42.880941+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.