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Formal Proofs of Orthogonality for Class-Incremental Learning for Wireless Device Identification in IoT
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  • Yongxin Liu ,
  • Jian Wang ,
  • Jianqiang Li ,
  • Shuteng Niu ,
  • Houbing Song
Yongxin Liu
Embry-Riddle Aeronautical University

Corresponding Author:[email protected]

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Jian Wang
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Jianqiang Li
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Shuteng Niu
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Houbing Song
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Abstract

This document provides a formal proof and supple- mentary information of the paper: Class-Incremental Learning for Wireless Device Identification in IoT. The original paper focuses on providing a novel and efficient incremental learning algorithm. In this document, we explicitly explain why the mem- ory representations (latent device fingerprints in our application) in Artificial Neural Networks approximate orthogonality with insights for the invention of our Channel Separation Incremental Learning algorithm.