Convolution (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Convolution" in English language version.

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15doi.org

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mathscinet.ams.org

Reed & Simon 1975, IX.4 Reed, Michael; Simon, Barry (1975), Methods of modern mathematical physics. II. Fourier analysis, self-adjointness, New York-London: Academic Press Harcourt Brace Jovanovich, Publishers, pp. xv+361, ISBN 0-12-585002-6, MR 0493420

archive.org

Press, William H.; Flannery, Brian P.; Teukolsky, Saul A.; Vetterling, William T. (1989). Numerical Recipes in Pascal. Cambridge University Press. p. 450. ISBN 0-521-37516-9.

books.google.com

R. N. Bracewell (2005), "Early work on imaging theory in radio astronomy", in W. T. Sullivan (ed.), The Early Years of Radio Astronomy: Reflections Fifty Years After Jansky's Discovery, Cambridge University Press, p. 172, ISBN 978-0-521-61602-7
John Hilton Grace and Alfred Young (1903), The algebra of invariants, Cambridge University Press, p. 40
Leonard Eugene Dickson (1914), Algebraic invariants, J. Wiley, p. 85, ISBN 978-1-4297-0042-9 {{citation}}: ISBN / Date incompatibility (help)

core.ac.uk

Bahri, Mawardi; Ashino, Ryuichi; Vaillancourt, Rémi (2013). "Convolution Theorems for Quaternion Fourier Transform: Properties and Applications" (PDF). Abstract and Applied Analysis. 2013: 1–10. doi:10.1155/2013/162769. Archived (PDF) from the original on 2020-10-21. Retrieved 2022-11-11.

doi.org

Bahri, Mawardi; Ashino, Ryuichi; Vaillancourt, Rémi (2013). "Convolution Theorems for Quaternion Fourier Transform: Properties and Applications" (PDF). Abstract and Applied Analysis. 2013: 1–10. doi:10.1155/2013/162769. Archived (PDF) from the original on 2020-10-21. Retrieved 2022-11-11.
Rader, C.M. (December 1972). "Discrete Convolutions via Mersenne Transforms". IEEE Transactions on Computers. 21 (12): 1269–1273. doi:10.1109/T-C.1972.223497. S2CID 1939809.
Winograd, Shmuel (January 1980). Arithmetic Complexity of Computations. Society for Industrial and Applied Mathematics. doi:10.1137/1.9781611970364. ISBN 978-0-89871-163-9.
Lyakhov, P. A.; Nagornov, N. N.; Semyonova, N. F.; Abdulsalyamova, A. S. (June 2023). "Reducing the Computational Complexity of Image Processing Using Wavelet Transform Based on the Winograd Method". Pattern Recognition and Image Analysis. 33 (2): 184–191. doi:10.1134/S1054661823020074. ISSN 1054-6618. S2CID 259310351.
Wu, Di; Fan, Xitian; Cao, Wei; Wang, Lingli (May 2021). "SWM: A High-Performance Sparse-Winograd Matrix Multiplication CNN Accelerator". IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 29 (5): 936–949. doi:10.1109/TVLSI.2021.3060041. ISSN 1063-8210. S2CID 233433757.
Mittal, Sparsh; Vibhu (May 2021). "A survey of accelerator architectures for 3D convolution neural networks". Journal of Systems Architecture. 115: 102041. doi:10.1016/j.sysarc.2021.102041. S2CID 233917781.
Beckner, William (1975). "Inequalities in Fourier analysis". Annals of Mathematics. Second Series. 102 (1): 159–182. doi:10.2307/1970980. JSTOR 1970980.
Brascamp, Herm Jan; Lieb, Elliott H. (1976). "Best constants in Young's inequality, its converse, and its generalization to more than three functions". Advances in Mathematics. 20 (2): 151–173. doi:10.1016/0001-8708(76)90184-5.
Slyusar, V. I. (March 13, 1998). "A Family of Face Products of Matrices and its Properties" (PDF). Cybernetics and Systems Analysis C/C of Kibernetika I Sistemnyi Analiz.- 1999. 35 (3): 379–384. doi:10.1007/BF02733426. S2CID 119661450. Archived (PDF) from the original on 2013-08-11.
Ninh, Pham; Pagh, Rasmus (2013). Fast and scalable polynomial kernels via explicit feature maps. SIGKDD international conference on Knowledge discovery and data mining. Association for Computing Machinery. doi:10.1145/2487575.2487591.
Zhang, Yingjie; Soon, Hong Geok; Ye, Dongsen; Fuh, Jerry Ying Hsi; Zhu, Kunpeng (September 2020). "Powder-Bed Fusion Process Monitoring by Machine Vision With Hybrid Convolutional Neural Networks". IEEE Transactions on Industrial Informatics. 16 (9): 5769–5779. doi:10.1109/TII.2019.2956078. ISSN 1941-0050. S2CID 213010088.
Chervyakov, N.I.; Lyakhov, P.A.; Deryabin, M.A.; Nagornov, N.N.; Valueva, M.V.; Valuev, G.V. (September 2020). "Residue Number System-Based Solution for Reducing the Hardware Cost of a Convolutional Neural Network". Neurocomputing. 407: 439–453. doi:10.1016/j.neucom.2020.04.018. S2CID 219470398. Convolutional neural networks represent deep learning architectures that are currently used in a wide range of applications, including computer vision, speech recognition, time series analysis in finance, and many others.
Diggle 1985. Diggle, P. J. (1985), "A kernel method for smoothing point process data", Journal of the Royal Statistical Society, Series C, 34 (2): 138–147, doi:10.2307/2347366, JSTOR 2347366, S2CID 116746157
Ghasemi & Nowak 2017. Ghasemi, S. Hooman; Nowak, Andrzej S. (2017), "Reliability Index for Non-normal Distributions of Limit State Functions", Structural Engineering and Mechanics, 62 (3): 365–372, doi:10.12989/sem.2017.62.3.365
Monaghan, J. J. (1992). "Smoothed particle hydrodynamics". Annual Review of Astronomy and Astrophysics. 30: 543–547. Bibcode:1992ARA&A..30..543M. doi:10.1146/annurev.aa.30.090192.002551. Retrieved 16 February 2021.

dspguide.com

Smith, Stephen W (1997). "13.Convolution". The Scientist and Engineer's Guide to Digital Signal Processing (1 ed.). California Technical Publishing. ISBN 0-9660176-3-3. Retrieved 22 April 2016.

elsevier.com

linkinghub.elsevier.com

Mittal, Sparsh; Vibhu (May 2021). "A survey of accelerator architectures for 3D convolution neural networks". Journal of Systems Architecture. 115: 102041. doi:10.1016/j.sysarc.2021.102041. S2CID 233917781.
Chervyakov, N.I.; Lyakhov, P.A.; Deryabin, M.A.; Nagornov, N.N.; Valueva, M.V.; Valuev, G.V. (September 2020). "Residue Number System-Based Solution for Reducing the Hardware Cost of a Convolutional Neural Network". Neurocomputing. 407: 439–453. doi:10.1016/j.neucom.2020.04.018. S2CID 219470398. Convolutional neural networks represent deep learning architectures that are currently used in a wide range of applications, including computer vision, speech recognition, time series analysis in finance, and many others.

gatech.edu

users.ece.gatech.edu

Juang, B.H. "Lecture 21: Block Convolution" (PDF). EECS at the Georgia Institute of Technology. Archived (PDF) from the original on 2004-07-29. Retrieved 17 May 2013.

harvard.edu

ui.adsabs.harvard.edu

Monaghan, J. J. (1992). "Smoothed particle hydrodynamics". Annual Review of Astronomy and Astrophysics. 30: 543–547. Bibcode:1992ARA&A..30..543M. doi:10.1146/annurev.aa.30.090192.002551. Retrieved 16 February 2021.

ieee.org

ieeexplore.ieee.org

Wu, Di; Fan, Xitian; Cao, Wei; Wang, Lingli (May 2021). "SWM: A High-Performance Sparse-Winograd Matrix Multiplication CNN Accelerator". IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 29 (5): 936–949. doi:10.1109/TVLSI.2021.3060041. ISSN 1063-8210. S2CID 233433757.
Zhang, Yingjie; Soon, Hong Geok; Ye, Dongsen; Fuh, Jerry Ying Hsi; Zhu, Kunpeng (September 2020). "Powder-Bed Fusion Process Monitoring by Machine Vision With Hybrid Convolutional Neural Networks". IEEE Transactions on Industrial Informatics. 16 (9): 5769–5779. doi:10.1109/TII.2019.2956078. ISSN 1941-0050. S2CID 213010088.

jstor.org

Beckner, William (1975). "Inequalities in Fourier analysis". Annals of Mathematics. Second Series. 102 (1): 159–182. doi:10.2307/1970980. JSTOR 1970980.
Diggle 1985. Diggle, P. J. (1985), "A kernel method for smoothing point process data", Journal of the Royal Statistical Society, Series C, 34 (2): 138–147, doi:10.2307/2347366, JSTOR 2347366, S2CID 116746157

mit.edu

ocw.mit.edu

Differential Equations (Spring 2010), MIT 18.03. "Lecture 21: Convolution Formula". MIT Open Courseware. MIT. Retrieved 22 December 2021.{{cite web}}: CS1 maint: numeric names: authors list (link)
"18.03SC Differential Equations Fall 2011" (PDF). Green's Formula, Laplace Transform of Convolution. Archived (PDF) from the original on 2015-09-06.

nips.cc

papers.nips.cc

Atlas, Homma, and Marks. "An Artificial Neural Network for Spatio-Temporal Bipolar Patterns: Application to Phoneme Classification" (PDF). Neural Information Processing Systems (NIPS 1987). 1. Archived (PDF) from the original on 2021-04-14.{{cite journal}}: CS1 maint: multiple names: authors list (link)

semanticscholar.org

api.semanticscholar.org

Rader, C.M. (December 1972). "Discrete Convolutions via Mersenne Transforms". IEEE Transactions on Computers. 21 (12): 1269–1273. doi:10.1109/T-C.1972.223497. S2CID 1939809.
Lyakhov, P. A.; Nagornov, N. N.; Semyonova, N. F.; Abdulsalyamova, A. S. (June 2023). "Reducing the Computational Complexity of Image Processing Using Wavelet Transform Based on the Winograd Method". Pattern Recognition and Image Analysis. 33 (2): 184–191. doi:10.1134/S1054661823020074. ISSN 1054-6618. S2CID 259310351.
Wu, Di; Fan, Xitian; Cao, Wei; Wang, Lingli (May 2021). "SWM: A High-Performance Sparse-Winograd Matrix Multiplication CNN Accelerator". IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 29 (5): 936–949. doi:10.1109/TVLSI.2021.3060041. ISSN 1063-8210. S2CID 233433757.
Mittal, Sparsh; Vibhu (May 2021). "A survey of accelerator architectures for 3D convolution neural networks". Journal of Systems Architecture. 115: 102041. doi:10.1016/j.sysarc.2021.102041. S2CID 233917781.
Slyusar, V. I. (March 13, 1998). "A Family of Face Products of Matrices and its Properties" (PDF). Cybernetics and Systems Analysis C/C of Kibernetika I Sistemnyi Analiz.- 1999. 35 (3): 379–384. doi:10.1007/BF02733426. S2CID 119661450. Archived (PDF) from the original on 2013-08-11.
Zhang, Yingjie; Soon, Hong Geok; Ye, Dongsen; Fuh, Jerry Ying Hsi; Zhu, Kunpeng (September 2020). "Powder-Bed Fusion Process Monitoring by Machine Vision With Hybrid Convolutional Neural Networks". IEEE Transactions on Industrial Informatics. 16 (9): 5769–5779. doi:10.1109/TII.2019.2956078. ISSN 1941-0050. S2CID 213010088.
Chervyakov, N.I.; Lyakhov, P.A.; Deryabin, M.A.; Nagornov, N.N.; Valueva, M.V.; Valuev, G.V. (September 2020). "Residue Number System-Based Solution for Reducing the Hardware Cost of a Convolutional Neural Network". Neurocomputing. 407: 439–453. doi:10.1016/j.neucom.2020.04.018. S2CID 219470398. Convolutional neural networks represent deep learning architectures that are currently used in a wide range of applications, including computer vision, speech recognition, time series analysis in finance, and many others.
Diggle 1985. Diggle, P. J. (1985), "A kernel method for smoothing point process data", Journal of the Royal Statistical Society, Series C, 34 (2): 138–147, doi:10.2307/2347366, JSTOR 2347366, S2CID 116746157

siam.org

epubs.siam.org

Winograd, Shmuel (January 1980). Arithmetic Complexity of Computations. Society for Industrial and Applied Mathematics. doi:10.1137/1.9781611970364. ISBN 978-0-89871-163-9.

slyusar.kiev.ua

Slyusar, V. I. (December 27, 1996). "End products in matrices in radar applications" (PDF). Radioelectronics and Communications Systems. 41 (3): 50–53. Archived (PDF) from the original on 2013-08-11.
Slyusar, V. I. (1997-05-20). "Analytical model of the digital antenna array on a basis of face-splitting matrix products" (PDF). Proc. ICATT-97, Kyiv: 108–109. Archived (PDF) from the original on 2013-08-11.
Slyusar, V. I. (1997-09-15). "New operations of matrices product for applications of radars" (PDF). Proc. Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory (DIPED-97), Lviv.: 73–74. Archived (PDF) from the original on 2013-08-11.
Slyusar, V. I. (March 13, 1998). "A Family of Face Products of Matrices and its Properties" (PDF). Cybernetics and Systems Analysis C/C of Kibernetika I Sistemnyi Analiz.- 1999. 35 (3): 379–384. doi:10.1007/BF02733426. S2CID 119661450. Archived (PDF) from the original on 2013-08-11.
Slyusar, V. I. (2003). "Generalized face-products of matrices in models of digital antenna arrays with nonidentical channels" (PDF). Radioelectronics and Communications Systems. 46 (10): 9–17. Archived (PDF) from the original on 2013-08-11.

springer.com

link.springer.com

Lyakhov, P. A.; Nagornov, N. N.; Semyonova, N. F.; Abdulsalyamova, A. S. (June 2023). "Reducing the Computational Complexity of Image Processing Using Wavelet Transform Based on the Winograd Method". Pattern Recognition and Image Analysis. 33 (2): 184–191. doi:10.1134/S1054661823020074. ISSN 1054-6618. S2CID 259310351.

ust.hk

cs.ust.hk

Gardner, William G. (November 1994). "Efficient Convolution without Input/Output Delay" (PDF). Audio Engineering Society Convention 97. Paper 3897. Archived (PDF) from the original on 2015-04-08. Retrieved 17 May 2013.

web.archive.org

Bahri, Mawardi; Ashino, Ryuichi; Vaillancourt, Rémi (2013). "Convolution Theorems for Quaternion Fourier Transform: Properties and Applications" (PDF). Abstract and Applied Analysis. 2013: 1–10. doi:10.1155/2013/162769. Archived (PDF) from the original on 2020-10-21. Retrieved 2022-11-11.
"18.03SC Differential Equations Fall 2011" (PDF). Green's Formula, Laplace Transform of Convolution. Archived (PDF) from the original on 2015-09-06.
Juang, B.H. "Lecture 21: Block Convolution" (PDF). EECS at the Georgia Institute of Technology. Archived (PDF) from the original on 2004-07-29. Retrieved 17 May 2013.
Gardner, William G. (November 1994). "Efficient Convolution without Input/Output Delay" (PDF). Audio Engineering Society Convention 97. Paper 3897. Archived (PDF) from the original on 2015-04-08. Retrieved 17 May 2013.
Slyusar, V. I. (December 27, 1996). "End products in matrices in radar applications" (PDF). Radioelectronics and Communications Systems. 41 (3): 50–53. Archived (PDF) from the original on 2013-08-11.
Slyusar, V. I. (1997-05-20). "Analytical model of the digital antenna array on a basis of face-splitting matrix products" (PDF). Proc. ICATT-97, Kyiv: 108–109. Archived (PDF) from the original on 2013-08-11.
Slyusar, V. I. (1997-09-15). "New operations of matrices product for applications of radars" (PDF). Proc. Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory (DIPED-97), Lviv.: 73–74. Archived (PDF) from the original on 2013-08-11.
Slyusar, V. I. (March 13, 1998). "A Family of Face Products of Matrices and its Properties" (PDF). Cybernetics and Systems Analysis C/C of Kibernetika I Sistemnyi Analiz.- 1999. 35 (3): 379–384. doi:10.1007/BF02733426. S2CID 119661450. Archived (PDF) from the original on 2013-08-11.
Slyusar, V. I. (2003). "Generalized face-products of matrices in models of digital antenna arrays with nonidentical channels" (PDF). Radioelectronics and Communications Systems. 46 (10): 9–17. Archived (PDF) from the original on 2013-08-11.
Atlas, Homma, and Marks. "An Artificial Neural Network for Spatio-Temporal Bipolar Patterns: Application to Phoneme Classification" (PDF). Neural Information Processing Systems (NIPS 1987). 1. Archived (PDF) from the original on 2021-04-14.{{cite journal}}: CS1 maint: multiple names: authors list (link)

wolfram.com

mathworld.wolfram.com

Weisstein, Eric W. "Convolution". mathworld.wolfram.com. Retrieved 2021-09-22.
Weisstein, Eric W. "From MathWorld--A Wolfram Web Resource".

worldcat.org

search.worldcat.org

Lyakhov, P. A.; Nagornov, N. N.; Semyonova, N. F.; Abdulsalyamova, A. S. (June 2023). "Reducing the Computational Complexity of Image Processing Using Wavelet Transform Based on the Winograd Method". Pattern Recognition and Image Analysis. 33 (2): 184–191. doi:10.1134/S1054661823020074. ISSN 1054-6618. S2CID 259310351.
Wu, Di; Fan, Xitian; Cao, Wei; Wang, Lingli (May 2021). "SWM: A High-Performance Sparse-Winograd Matrix Multiplication CNN Accelerator". IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 29 (5): 936–949. doi:10.1109/TVLSI.2021.3060041. ISSN 1063-8210. S2CID 233433757.
Zhang, Yingjie; Soon, Hong Geok; Ye, Dongsen; Fuh, Jerry Ying Hsi; Zhu, Kunpeng (September 2020). "Powder-Bed Fusion Process Monitoring by Machine Vision With Hybrid Convolutional Neural Networks". IEEE Transactions on Industrial Informatics. 16 (9): 5769–5779. doi:10.1109/TII.2019.2956078. ISSN 1941-0050. S2CID 213010088.