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A dictionary learning algorithm for denoising polynomial phase signal based on neural networks.

• Authors : Ou, Guojian (AUTHOR); Zou, Sai (AUTHOR); Liu, Song (AUTHOR)

Subjects: MACHINE learning; ADDITIVE white Gaussian noise

• Source: Neural Computing & Applications. Aug2023, Vol. 35 Issue 22, p16341-16355. 15p.

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Computationally Efficient Wideband Spectrum Sensing through Cumulative Distribution Function and Machine Learnin.

• Authors : Nikonowicz, Jakub; Jessa, Mieczysław; Matuszewski, IEEE,,Łukasz

Subjects: ADDITIVE white Gaussian noise; FAST Fourier transforms; MACHINE theory

• Source: Journal of Communications Software & Systems; Mar2024, Vol. 20 Issue 1, p38-46, 9p

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Transfer learning evaluation based on optimal convolution neural networks architecture for bearing fault diagnosis applications.

• Authors : Alabsi, Mohammed; Pearlstein, Larry; Nalluri, Nithya

Subjects: CONVOLUTIONAL neural networks; FAULT diagnosis; MACHINE learning

• Source: Journal of Vibration & Control; Mar2024, Vol. 30 Issue 5/6, p1013-1022, 10p

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Applied Science & Technology Full Text (H.W. Wilson)

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An efficient soft demapper for APSK signals using extreme learning machine.

• Authors : Öztekin, Abdulkerim (AUTHOR); Erçelebi, Ergun (AUTHOR)

Subjects: ADDITIVE white Gaussian noise channels; MACHINE learning; PHASE shift keying

• Source: Neural Computing & Applications. Oct2019, Vol. 31 Issue 10, p5715-5727. 13p.

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Applied Science & Technology Full Text (H.W. Wilson)

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Applied Science & Technology Full Text (H.W. Wilson)

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DDPG with Transfer Learning and Meta Learning Framework for Resource Allocation in Underlay Cognitive Radio Network.

• Authors : Mishra, Nikita; Srivastava, Sumit; Sharan, Shivendra Nath

Subjects: COGNITIVE radio; RADIO networks; ADDITIVE white Gaussian noise

• Source: Wireless Personal Communications; May2023, Vol. 130 Issue 2, p729-755, 27p

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Editorial for the Special Issue "Advances in Machine Learning and Mathematical Modeling for Optimization Problems".

• Authors : Chehri, Abdellah; Rivest, Francois

Subjects: MATHEMATICAL models; DEEP learning; MACHINE learning

• Source: Mathematics (2227-7390); Apr2023, Vol. 11 Issue 8, p1890, 5p

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Hybrid data augmentation method for combined failure recognition in rotating machines.

• Authors : Martins, Dionísio H. C. S. S.; de Lima, Amaro A.; Pinto, Milena F.

Subjects: DATA augmentation; ADDITIVE white Gaussian noise; MACHINE learning

• Source: Journal of Intelligent Manufacturing; Apr2023, Vol. 34 Issue 4, p1795-1813, 19p

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