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- No longer published by Cambridge University Press
- ISSN: 2048-7703 (Online)
Asia-Pacific Signal and Information Processing Association (APSIPA) serves as an international forum for signal and information processing researchers across a broad spectrum of research, ranging from traditional modalities of signal processing to emerging areas where either (i) processing reaches higher semantic levels (e.g., from speech recognition to multimodal human behaviour recognition) or (ii) processing is meant to extract information from datasets that are not traditionally considered signals (e.g., mining of Internet or sensor information).
Cambridge University Press ceases publication of APSIPA Transactions on Signal and Information Processing on completion of Volume 10. From Volume 11 the Journal will be published by NOW Publishers. Please visit the new website at: https://www.nowpublishers.com/SIP
Cambridge University Press ceases publication of APSIPA Transactions on Signal and Information Processing on completion of Volume 10. From Volume 11 the Journal will be published by NOW Publishers. Please visit the new website at: https://www.nowpublishers.com/SIP
Latest articles
News
Themed Series: Multi-Disciplinary Dis/Misinformation Analysis and Countermeasures
- 19 May 2021,
- Themed Series of APSIPA Transactions on Signal and Information Processing on “Multi-Disciplinary Dis/Misinformation Analysis and Countermeasures”
Engineering « Cambridge Core Blog
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Best practices in the use of an airborne teaching laboratory
- 14 September 2023,
- This post introduces the paper 'Establishing best practices in the use of an airborne teaching laboratory'
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2023 JFM-Flow China Symposium: from fundamentals to applied mechanics
- 13 September 2023,
- We were excited to hold the JFM/FLOW 2023 China Symposium in Hefei in July 2023
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Damper model identification using mixed physical and machine-learning-based approach
- 21 August 2023,
- This post introduces an AER paper that aims to demonstrate the applicability of a machine learning method to identify a nonlinear model of a physical component...
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