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Learning from data in the quaternion domain enables us to exploit internal dependencies of 4D signals and treating them as a single entity.
Quaternions and Caley Numbers. Algebra ans Applications
J. P. Ward, · 1997
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“Immersive audio schemes,”
Y. Huang, J. Chen, and J. Benesty, · 2011
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“Intelligent acoustic interfaces for immersive audio,”
D. Comminiello, M. Scarpiniti, R. Parisi, and A. Uncini, · 2013
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“Intelligent acoustic interfaces with multisensor acquisition for immersive reproduction,”
D. Comminiello, S. Cecchi, M. Scarpiniti, M. Gasparini, L. Romoli, F. Piazza, and A. Uncini, · 2015
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“Delving deep into rectifiers: Surpassing human-level performance on ImageNet classification,”
K. He, X. Zhang, S. Ren, and J. Sun, · 2015
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“The widely linear block quaternion least mean square algorithm for fast computation in 3D audio systems,”
F. Ortolani, D. Comminiello, and A. Uncini, · 2016
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“Advances in hypercomplex adaptive filtering for 3D audio processing,”
F. Ortolani, D. Comminiello, M. Scarpiniti, and A. Uncini, · 2017
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“Frequency domain quaternion adaptive filters: Algorithms and convergence performance,”
F. Ortolani, D. Comminiello, M. Scarpiniti, and A. Uncini, · 2017
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“Widely linear quaternion unscented Kalman filter for quaternion-valued feedforward neural network,”
L. Xiaodong, L. Aijun, Y. Changjun, and S. Fulin, · 2017
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“Feed forward neural network with random quaternionic neurons,”
T. Minemoto, T. Isokawa, H. Nishimura, and N. Matsui, · 2017
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“Broadband DOA estimation using convolutional neural networks trained with noise signals,”
S. Chakrabarty and E. A. P. Habets, · 2017
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“Sound event detection using spatial features and convolutional recurrent neural network,”
S. Adavanne, P. Pertilä, and T. Virtanen, · 2017
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“Convolutional recurrent neural networks for polyphonic sound event detection,”
E. Çakır, G. Parascandolo, T. Heittola, H. Huttunen, and T. Virtanen, · 2017
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“Audio event detection using multiple-input convolutional neural network,”
I.-Y. Jeong, S. Lee, Y. Han, and K. Lee, · 2017
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“Signal processing supports a new wave of audio research: Spatial and immersive audio mimics real-world sound environments,”
J. Edwards, · 2018
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“Quaternion adaptive line enhancer based on singular spectrum analysis,”
S. Sanei, C. C. Took, and S. Enshaeifar, · 2018
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“Two-dimensional quaternion sparse principle component analysis,”
X. Xiao and Y. Zhou, · 2018
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“Deep quaternion networks,”
C. Gaudet and A. Maida, · 2018
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“Quaternion recurrent neural networks,”
T. Parcollet, M. Ravanelli, M. Morchid, G. Linarès, C. Trabelsi, R. De Mori, and Y. Bengio, · 2018
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“Quaternion convolutional neural networks for end-to-end automatic speech recognition,”
T. Parcollet, Y. Zhang, M. Morchid, C. Trabelsi, G. Linar‘es, R. De Mori, and Y. Bengio, · 2018
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“Sound source localization in a multipath environment using convolutional neural networks,”
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T. Mizoguchi and I. Yamada, · 2018
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“Performance analysis of quaternion-valued adaptive filters in nonstationary environments,”
M. Xiang, S. Kanna, and D. P. Mandic, · 2018
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“A quaternion kernel minimum error entropy adaptive filter,”
T. Ogunfunmi and C. Safarian, · 2018
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Adaptive Learning Methods for Nonlinear System Modeling
Y. Xia, M. Xiang, Z. Li, and D. P. Mandic, · 2018
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E. L. Ferguson, S. B. Williams, and C. T. Jin, · 2018
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“Spatial audio feature discovery with convolutional neural networks,”
E. Thuillier, H. Gamper, and I. J. Tashev, · 2018
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“Direction of arrival estimation for multiple sound sources using convolutional recurrent neural networks,”
S. Adavanne, A. Politis, and T. Virtanen, · 2018
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S. Adavanne, A. Politis, J. Nikunen, and T. Virtanen, · 2018
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