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Signal theory for SVM kernel parameter estimation

Signal theory for SVM kernel parameter estimation
Signal theory for SVM kernel parameter estimation
149-154
Nelson, J. D. B.
3bef57a7-4c0e-4501-bea7-0e528bcd64a2
Damper, R. I.
6e0e7fdc-57ec-44d4-bc0f-029d17ba441d
Gunn, S. R.
306af9b3-a7fa-4381-baf9-5d6a6ec89868
Guo, B.
6c4581ac-e3e3-4002-992a-3abb7776ec5d
Nelson, J. D. B.
3bef57a7-4c0e-4501-bea7-0e528bcd64a2
Damper, R. I.
6e0e7fdc-57ec-44d4-bc0f-029d17ba441d
Gunn, S. R.
306af9b3-a7fa-4381-baf9-5d6a6ec89868
Guo, B.
6c4581ac-e3e3-4002-992a-3abb7776ec5d

Nelson, J. D. B., Damper, R. I., Gunn, S. R. and Guo, B. (2006) Signal theory for SVM kernel parameter estimation. IEEE International Workshop on Machine Learning for Signal Processing, Maynooth, Ireland. pp. 149-154 .

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Published date: 2006
Venue - Dates: IEEE International Workshop on Machine Learning for Signal Processing, Maynooth, Ireland, 2006-09-01
Organisations: Electronic & Software Systems, Southampton Wireless Group

Identifiers

Local EPrints ID: 262729
URI: http://eprints.soton.ac.uk/id/eprint/262729
PURE UUID: 3e97e922-fb51-4aab-9add-762bbb57ab52

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Date deposited: 19 Jun 2006
Last modified: 14 Mar 2024 07:16

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Contributors

Author: J. D. B. Nelson
Author: R. I. Damper
Author: S. R. Gunn
Author: B. Guo

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