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Letter on Convergence of In-Parameter-Linear Nonlinear Neural Architectures With Gradient Learnings.

, , , , and . IEEE Trans. Neural Networks Learn. Syst., 34 (8): 5189-5192 (August 2023)

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Higher Order Neural Units for Efficient Adaptive Control of Weakly Nonlinear Systems., , , and . IJCCI, page 149-157. SciTePress, (2017)Improved Tumor Image Estimation in X-Ray Fluoroscopic Images by Augmenting 4DCT Data for Radiotherapy., , , , , , and . J. Adv. Comput. Intell. Intell. Informatics, 26 (4): 471-482 (2022)A Letter on Convergence of In-Parameter-Linear Nonlinear Neural Architectures with Gradient Learnings., , , , and . CoRR, (2021)Deep Learning-Based Interpretable Computer-Aided Diagnosis of Drowning for Forensic Radiology., , , , , , and . SICE, page 820-824. IEEE, (2021)Intelligent sensing of biomedical signals - Lung tumor motion prediction for accurate radiotherapy., , , and . CompSens, page 35-41. IEEE, (2011)A 2.5D Deep Learning-Based Method for Drowning Diagnosis Using Post-Mortem Computed Tomography., , , , , , and . IEEE J. Biomed. Health Informatics, 27 (2): 1026-1035 (February 2023)How Different Data Sources Impact Deep Learning Performance in COVID-19 Diagnosis using Chest X-ray Images., , , , , and . IIAI-AAI, page 508-513. IEEE, (2023)Framework for Discrete-Time Model Reference Adaptive Control of Weakly Nonlinear Systems with HONUs., , , , , and . IJCCI (Selected Papers), volume 829 of Studies in Computational Intelligence, page 239-262. Springer, (2017)Tumor motion tracking using kV/MV X-ray fluoroscopy for adaptive radiation therapy., , , , , , , and . IWCIM, page 1-4. IEEE, (2015)Study of Learning Entropy for Novelty Detection in lung tumor motion prediction for target tracking radiation therapy., , , and . IJCNN, page 3124-3129. IEEE, (2014)