gedisentangleerd
Gedisentangleerd is a term used in Dutch-language discussions of data science, information theory, and narrative analysis to describe both the process and the outcome of disentangling previously entangled components. It denotes the separation of intertwined factors, signals, or ideas into more independent or coherently related elements, enabling clearer analysis and interpretation.
Etymology: It is a neologism formed by combining the English verb disentangle with the Dutch past participle
Applications: In sensor networks and audio processing, gedisentangleerd refers to separating mixed signals into their sources.
Methods: Achieving a gedisentangleerd state commonly relies on algorithms such as independent component analysis (ICA), principal
Relation: The concept overlaps with established ideas of disentangled representations in machine learning and with the
See also: disentangled representations; independent component analysis; blind source separation; factor analysis; tensor decomposition; nonnegative matrix