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The space of good ideas may be finite, while the names we give these ideas are infinite. There are many examples of redundant nomenclature. Just open the Wikipedia entry on Principal Component Analysis, to realize it was discovered and rediscovered under the names Discrete Karhunen–Loève Transform; Hotelling Transform; Proper Orthogonal Decomposition; Eckart–Young Theorem; Schmidt–Mirsky Theorem; Empirical Orthogonal Functions; Empirical Eigenfunction Decomposition; Empirical Component Analysis; Quasi-Harmonic Modes; Spectral Decomposition; Empirical Modal Analysis, and possibly more.
This terminological divergence is also found in signal processing. Here are some examples.
Terminological divergence creates barriers. Cynicists will consider these barriers welcome: they allow us to rediscover the discovered. Most, however, will consider the unwelcome, since they impede the exchange of ideas.
There are two main approaches to eliminating communal barriers such as language: homogenize, and teach. By homogenization we refer to the idea of converging to a unified language. Klein's Encyclopedia of Mathematical Sciences served to homogenize mathematical terminology, which was diverging in the early 20’th century. This author prefers the teaching approach: where we introduce the diverging terminologies in our teaching. This will allow students and practitioners to navigate the vast realms of existing literature, and converse with colleagues in other disciplines. Much like a tradesman that trades goods between communities, we should allow practitioners to trade ideas.
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Call for Nominations: IEEE Technical Field Awards | 15 January 2025 |
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Nominate an IEEE Fellow Today! | 7 February 2025 |
Call for Nominations for IEEE SPS Editors-in-Chief | 10 February 2025 |
Call for Nominations for IEEE SPS Editors-in-Chief | 10 February 2025 |
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