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Paper Citation Record · LEDGER

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection

As of 22 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2607.15441.

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

pith.paper-citation-record.v1
2607.15441 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T23:25:23.185600Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

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Reference resolution

18 of 18 outbound references displayed

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External citation measurements

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Outbound references

Observation e1145a76-e236-4770-82f0-0603bb866327 · outbound

This paper cites 6G Wireless Communicati ons in 7–24 GHz Band: Opportunities, Techniques, and Challenges,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection 6G Wireless Communicati ons in 7–24 GHz Band: Opportunities, Techniques, and Challenges,

Reference 1

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Observation d635748b-3374-4972-9e6b-f6033f467e17 · outbound

This paper cites Digital P redistortion Linearization Demystified: Insights Y ou Always Wanted to Kn ow but Were Too Linear to Ask,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection Digital P redistortion Linearization Demystified: Insights Y ou Always Wanted to Kn ow but Were Too Linear to Ask,

Reference 2

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Observation ab2d7a9d-6588-4d94-b42d-195266ce5b4e · outbound

This paper cites A Gen eralized Memory Polynomial Model for Digital Predistortion of RF Pow er Amplifiers,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection A Gen eralized Memory Polynomial Model for Digital Predistortion of RF Pow er Amplifiers,

Reference 3

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Observation 2174ff06-1e68-4bda-bc18-94072ae2d2a8 · outbound

This paper cites Dynamic behavio ral modeling of 3G power amplifiers using real-valued time-delay neural n etworks,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection Dynamic behavio ral modeling of 3G power amplifiers using real-valued time-delay neural n etworks,

Reference 4

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Observation 30bec0b6-b508-4320-b596-b5eed0439008 · outbound

This paper cites Dee p Neural Network-Based Digital Predistorter for Doherty Power Ampl ifiers,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection Dee p Neural Network-Based Digital Predistorter for Doherty Power Ampl ifiers,

Reference 5

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Observation 966499ed-7664-41d4-8738-8a2bec57cbc7 · outbound

This paper cites Next-Gen Digital P redistortion From Hardware Acceleration of Neural Networks: Trends, Cha llenges, and Future,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection Next-Gen Digital P redistortion From Hardware Acceleration of Neural Networks: Trends, Cha llenges, and Future,

Reference 6

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Observation 2db70327-42cd-4676-8bb5-06e4b574be05 · outbound

This paper cites Res idual Neural Networks for Digital Predistortion,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection Res idual Neural Networks for Digital Predistortion,

Reference 7

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Observation 48747ee4-5a90-49c0-9032-b839f4fd6697 · outbound

This paper cites Phase- Normalized Neural Network for Linearization of RF Power Amp lifiers,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection Phase- Normalized Neural Network for Linearization of RF Power Amp lifiers,

Reference 8

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Observation b3fa39d1-da9c-4873-84ee-e722622c67c1 · outbound

This paper cites OpenDPD: An Open-Source End-to-End Learning & Benchmarking Framework for Wideband Power Amplifier Modeli ng and Digital Pre-Distortion,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection OpenDPD: An Open-Source End-to-End Learning & Benchmarking Framework for Wideband Power Amplifier Modeli ng and Digital Pre-Distortion,

Reference 9

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source=pdf_text observed=2026-08-01T23:25:22.127029Z digest=sha256:e3a131081528c4c27e7974dc59280af2f077c9b5d1300b6ec3a7f856dd29aad1

Observation 164d6fab-d9f4-42c7-892c-afedbbb526f9 · outbound

This paper cites A comparative analysis of the complexity/accura cy tradeoff in power amplifier behavioral models,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection A comparative analysis of the complexity/accura cy tradeoff in power amplifier behavioral models,

Reference 10

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Observation 82542bd5-b452-4659-a090-1396efcf9b25 · outbound

This paper cites Behavioral Power A mplifier Model- ing Using the LASSO,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection Behavioral Power A mplifier Model- ing Using the LASSO,

Reference 11

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Observation 1a5f1651-a059-4306-9dcf-9fd14ea38839 · outbound

This paper cites Compa rison of Feature Selection Techniques for Power Amplifier Behaviora l Modeling and Digital Predistortion Linearization,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection Compa rison of Feature Selection Techniques for Power Amplifier Behaviora l Modeling and Digital Predistortion Linearization,

Reference 12

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Observation 5a2c453a-8848-4780-8dbb-39988b56e7aa · outbound

This paper cites Feature selection based o n mu- tual information criteria of max-dependency, max-relevan ce, and min- redundancy,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection Feature selection based o n mu- tual information criteria of max-dependency, max-relevan ce, and min- redundancy,

Reference 13

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Observation de7336c1-05da-4689-8b07-c3c64b7b0634 · outbound

This paper cites FR3 PA response dataset for behavioral modelling and digit al predis- tortion,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection FR3 PA response dataset for behavioral modelling and digit al predis- tortion,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 265fbc93-4077-4b6a-8231-78fea521e9ba · outbound

This paper cites A new V olterra predistorter based on the indirect learning architecture,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection A new V olterra predistorter based on the indirect learning architecture,

Reference 15

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Observation beefb955-f8c1-4df9-ab3b-8095f4883d49 · outbound

This paper cites The Evolution of V ec tor Network Analyzers to Provide Precision V ector Spectrum Analysis fo r 6G Applications: VNA Evolves for 6G EVM Signals,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection The Evolution of V ec tor Network Analyzers to Provide Precision V ector Spectrum Analysis fo r 6G Applications: VNA Evolves for 6G EVM Signals,

Reference 16

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Observation 6f26c151-f310-4bc3-8650-73bac8a7564a · outbound

This paper cites Accurate hyperbolic tangent computati on,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection Accurate hyperbolic tangent computati on,

Reference 17

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Observation e229a4af-1c51-4498-96fb-5f1f24d2d2c9 · outbound

This paper cites Practical Bay esian Op- timization of Machine Learning Algorithms,.

Low Complexity Neural Network Digital Predistortion of Wideband Power Amplifiers through Feature Selection Practical Bay esian Op- timization of Machine Learning Algorithms,

Reference 18

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Pith citing papers

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