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Non-linear Schemes for Representation

Murty, M and Avinash, M (2023) Non-linear Schemes for Representation. [Book Chapter]

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Official URL: https://doi.org/10.1007/978-981-19-7908-8_5


In this chapter we deal with various nonlinear feature extraction schemes. In nonlinear feature extraction, the extracted features may be viewed as nonlinear combinations of the originally given features. Two popular neural network architectures employed are self-organizing map (SOM) and autoencoder (AE). We examine both of them in this chapter.

Item Type: Book Chapter
Publication: SpringerBriefs in Computer Science
Publisher: Springer
Additional Information: The copyright for this article belongs to Springer.
Keywords: Conformal mapping; Extraction; Feature extraction; Network architecture, Auto encoders; Given features; Neural network architecture; Non linear; Nonlinear combination; Nonlinear feature extraction; Self-organizing-maps, Self organizing maps
Department/Centre: Division of Electrical Sciences > Computer Science & Automation
Date Deposited: 20 May 2023 04:38
Last Modified: 20 May 2023 04:38
URI: https://eprints.iisc.ac.in/id/eprint/81578

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