Kumar, V and Patra, SK (2021) Feature Engineering for Machine Learning and Deep Learning Assisted Wireless Communication. [Book Chapter]
Full text not available from this repository.Abstract
Feature engineering involves extracting information from raw-data to use in machine learning or deep learning algorithms through feature transformation, feature generation or feature extraction, feature construction, feature selection, etc. Feature engineering optimizes the feature space dimensions, thereby reducing complexity. Hence, makes the data suitable for machine learning or deep learning applications: process prediction, detection accuracy, estimation accuracy, and quality of clustering and classi cation. Traditionally machine learning algorithms have been used in various wireless communication appli cations viz spectrum access and sharing, resource allocation, spectrum coverage, capacity optimization, signal intelligence, etc. This chapter presents the need for feature engineering and its application to machine learning and deep learning in wireless communication. The chapter also gives the details of the feature engineering assisted machine-learning algorithm for automatic modulation classi cation and path-loss prediction in wireless communication. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
| Item Type: | Book Chapter |
|---|---|
| Publication: | Studies in Computational Intelligence |
| Publisher: | Springer Science and Business Media Deutschland GmbH |
| Additional Information: | The copyright for this article belongs to Springer Science and Business Media Deutschland GmbH |
| Department/Centre: | Division of Electrical Sciences > Electrical Communication Engineering |
| Date Deposited: | 28 Nov 2021 09:21 |
| Last Modified: | 28 Nov 2021 09:21 |
| URI: | http://eprints.iisc.ac.in/id/eprint/69963 |
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