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Paper Citation Record · LEDGER

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling

As of 17 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2412.00070.

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

pith.paper-citation-record.v1
2412.00070 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:42:36.476148Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

29 of 29 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f15c6c1d-37bc-4193-8843-4c987fefc3ea · outbound

This paper cites A survey on deep learning for data-driven soft sensors,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling A survey on deep learning for data-driven soft sensors,

Reference 1

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Observation 6375ae93-ed08-435b-b96d-78fbd3262f48 · outbound

This paper cites Fuzzy adaptive knowledge-based inference neural networks: design and anal- ysis,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Fuzzy adaptive knowledge-based inference neural networks: design and anal- ysis,

Reference 2

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Observation e3453319-01dd-4ac2-8c5e-6001a1a55ad7 · outbound

This paper cites A learning con- volutional neural network approach for network robustness prediction,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling A learning con- volutional neural network approach for network robustness prediction,

Reference 3

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Observation 4ac3a78d-a892-416e-aa5d-71286b26854d · outbound

This paper cites Identification of nonlinear output-affine systems using an orthogonal least squares algorithm,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Identification of nonlinear output-affine systems using an orthogonal least squares algorithm,

Reference 4

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Observation 17e38181-fcfa-43f7-abe3-56061d80877e · outbound

This paper cites Ensemble stochastic configuration networks for estimating prediction intervals: a simultaneous robust training algorithm and its application,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Ensemble stochastic configuration networks for estimating prediction intervals: a simultaneous robust training algorithm and its application,

Reference 6

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Observation 7b420ab6-7d83-414d-b95f-d5124b8eef9a · outbound

This paper cites Recurrent Neural Networks and Long Short-Term Memory Networks: Tutorial and Survey.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Recurrent Neural Networks and Long Short-Term Memory Networks: Tutorial and Survey

Reference 7

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Source-reported events for the cited work

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Observation 63a61299-555b-4621-935a-f82ada8c33b8 · outbound

This paper cites Hybrid recurrent neural network architecture-based intention recognition for human–robot col- laboration,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Hybrid recurrent neural network architecture-based intention recognition for human–robot col- laboration,

Reference 8

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Observation e5aacb8a-2b50-4e97-bbf5-2c5041a247f2 · outbound

This paper cites Recurrent neural network training with convex loss and regularization functions by extended kalman filtering,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Recurrent neural network training with convex loss and regularization functions by extended kalman filtering,

Reference 9

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Source-reported events for the cited work

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Observation fdaf9a81-8c6a-43eb-b018-9ec54cbe8da2 · outbound

This paper cites Functional-link net computing: Theory, system architecture, and functionalities,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Functional-link net computing: Theory, system architecture, and functionalities,

Reference 10

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Source-reported events for the cited work

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Observation 39a0b751-39ca-4854-bd8c-07f9e65f3dad · outbound

This paper cites The echo state approach to analysing and training recurrent neural networks-with an erratum note,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling The echo state approach to analysing and training recurrent neural networks-with an erratum note,

Reference 11

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Source-reported events for the cited work

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Observation a0e3b534-e7b5-4fd1-8fa9-a5efb3bd2e73 · outbound

This paper cites Randomness in neural networks: an overview,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Randomness in neural networks: an overview,

Reference 12

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Observation d42390de-415b-44df-bee4-e926d4e32a98 · outbound

This paper cites Editorial: Randomized algorithms for training neural net- works,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Editorial: Randomized algorithms for training neural net- works,

Reference 13

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Observation df156eee-ba3d-4c50-9e7d-92ce2e900e06 · outbound

This paper cites Optimization and applications of echo state networks with leaky-integrator neurons,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Optimization and applications of echo state networks with leaky-integrator neurons,

Reference 14

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Observation 611d3f6f-421c-498c-b48d-f086792e7324 · outbound

This paper cites Pruning and regularization in reservoir computing,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Pruning and regularization in reservoir computing,

Reference 15

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Source-reported events for the cited work

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Observation 53cf1859-bfdc-4b4c-bc1f-886d726e2771 · outbound

This paper cites Dynamical regularized echo state network for time series prediction,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Dynamical regularized echo state network for time series prediction,

Reference 16

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Source-reported events for the cited work

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Observation a54d4980-ea5e-492b-821f-2333cd613251 · outbound

This paper cites A decentralized training algorithm for echo state networks in distributed big data applications,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling A decentralized training algorithm for echo state networks in distributed big data applications,

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation d84c63ab-8631-4642-808c-65244f5aa461 · outbound

This paper cites Stochastic configuration networks: Fundamentals and algorithms,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Stochastic configuration networks: Fundamentals and algorithms,

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 5bcc00b2-4418-45b8-8c7f-a97bc66a8368 · outbound

This paper cites Multitarget stochastic config- uration network and applications,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Multitarget stochastic config- uration network and applications,

Reference 19

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Observation 114cc11f-90f4-4540-bdc2-74796f8e3e6a · outbound

This paper cites A sparse learning method for SCN soft measurement model,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling A sparse learning method for SCN soft measurement model,

Reference 20

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Source-reported events for the cited work

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Observation cbce17b7-2bce-406f-a56e-373d1d61b27e · outbound

This paper cites A regularized stochastic configuration network based on weighted mean of vectors for regres- sion,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling A regularized stochastic configuration network based on weighted mean of vectors for regres- sion,

Reference 21

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Source-reported events for the cited work

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Observation 08ec9d29-c93f-4ea6-98a4-66fc8bd47167 · outbound

This paper cites Recurrent Stochastic Configuration Networks for Temporal Data Analytics.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Recurrent Stochastic Configuration Networks for Temporal Data Analytics

Reference 22

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Observation 3c72bde1-4a7d-43b1-8f58-fd450861bd2a · outbound

This paper cites Time-varying input and state delay compensation for uncertain nonlinear systems,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Time-varying input and state delay compensation for uncertain nonlinear systems,

Reference 23

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Source-reported events for the cited work

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Observation eccc9e93-eadd-4820-a29d-edde0a2b420b · outbound

This paper cites Dynamic gain reduced-order observer- based global adaptive neural-network tracking control for nonlinear time-delay systems,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Dynamic gain reduced-order observer- based global adaptive neural-network tracking control for nonlinear time-delay systems,

Reference 24

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Source-reported events for the cited work

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Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Regression shrinkage and selection via the lasso,

Reference 25

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Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Regularization and variable selection via the elastic net,

Reference 26

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Source-reported events for the cited work

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This paper cites Predicting particle size of copper ore grinding with stochastic configuration networks,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Predicting particle size of copper ore grinding with stochastic configuration networks,

Reference 27

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Source-reported events for the cited work

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Observation 14ad9293-40cb-4d10-806c-87c1b1bb58f7 · outbound

This paper cites Adaptive filtering prediction and control,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Adaptive filtering prediction and control,

Reference 28

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Source-reported events for the cited work

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Observation d7618faa-1080-4bdb-99e9-e09b2475fa87 · outbound

This paper cites Soft sensors for product quality monitoring in debutanizer distillation columns,.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Soft sensors for product quality monitoring in debutanizer distillation columns,

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation cb1f6e21-1823-4d82-894e-8e1db19aabd5 · outbound

This paper cites Recurrent Stochastic Configuration Networks with Incremental Blocks.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Recurrent Stochastic Configuration Networks with Incremental Blocks

Reference 30

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Source-reported events for the cited work

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