Information: Α physical reality or a humanly tool? From the model order to the appropriate number of clusters


Published: Dec 23, 2024
Keywords:
information model order K-means clustering
Markos Dendrinos
Abstract

This paper is a presentation of two important types of information regarding natural signals and groups of relative things. The measure of the first information type is the order of the system that produces the signal, while the second one is the appropriate number of distinct clusters for the most effective classification of a certain group into narrower and more representative subgroups. Firstly a review is given concerning the two approaches, and then a certain method is proposed for the identification of the correct number of clusters to be used in K-Means clustering process. The two information measures, model order and number of clusters, can be considered as two equivalent views of an inherent natural element, an objective order behind any physical system.

Article Details
  • Section
  • Research Articles
References
Bakamidis, S.; Dendrinos, M. and Carayannis, G., “SVD Analysis by Synthesis of Harmonic Signals”, Αcoustics Speech and Signal Processing (ASSP), IEEE, Vol. 39, No.2, pp. 472-477, Feb. 1991, https://ieeexplore.ieee.org/document/80831
Balasubramanian, S.; Rajavel, R.; Kar, Asuthos, “Ideal ratio mask estimation based on cochleagram for audio-visual monaural speech enhancement”, Applied Acoustics, Volume 211, August 2023.
Carayannis, G. and Gueguen, C. "The factorial linear modelling : a Karhunen-Loeve approach to speech analysis", Proc. IEEE Int. Conf. Acoust. Speech Signal Process., ICASSP, 1976, pp. 489-492.
Capurro, R., “Foundations of Information Science, Review and Perspectives”, International Conference on Conceptions of Library and Information Science, University of Tampere, Tampere, Finland, 26-28 August 1991. Also available at www.capurro.de/tampere91.htm
Capurro, R., “On the genealogy of information”, International Conference: Information. New Questions to a Multidisciplinary Concept, organized by the Chair for Philosophy of Technology at the Technical University of Cottbus held from March 1st to 3rd, 1994. Berlin: Akademic Verlag Berlin, 1996, pp. 259-270, also available at www.capurro.de/cottinf.htm
Christensen, Knud B.; Christensen, Mads G.; Boldt Jesper B.; Gran, Fredrik, “Experimental study of generalized subspace filters for the cocktail party situation”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 20-25 March 2016.
Dendrinos, M., “From the physical reality to the virtual reality in the library environment”, Library Philosophy and Practice (LPP) Journal, Vol. 7, No. 2, Spring 2005 https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1015&context=libphilprac
Dendrinos, M., “Obstructive Sleep Apnea (OSA) Detection through Energy and Spectral Measures”, International Conference on Signal Processing Applications and Technology (ICSPAT-98), IEEE, Toronto, Sept. 1998.
Dendrinos, Μ.; Bakamidis, S. and Carayannis G., “Speech Enhancement from Noise : A Regenerative Approach”, Speech Communication, Vol.10, No.1, pp.45-57, Feb.1991 http://www.sciencedirect.com/science/article/pii/016763939190027Q
Deppisch, Thomas; Amengual, Sebastià V.; Calamia, Garí Paul; Ahrens, Jens “Direct and Residual Subspace Decomposition of Spatial Room Impulse Responses”, IEEE/ACM Transactions on Audio, Speech and Language Processing, Volume 31, 2023, pp 927–942.
Fisher, R.A. "The use of multiple measurements in taxonomic problems", Annual Eugenics, 7, Part II, 179-188 (1936); also in Contributions to Mathematical Statistics (John Wiley, NY, 1950).
Foley, James D. and Van Dam, Andries, Fundamentals of Interactive Computer Graphics, Addison-Wesley Publishing Company, 1982.
Rao, S. S. and Gnanapmkasam, D. C., “A criterion for identifying dominant si¡igu1ar values in the SVD based method of harmonic retrieval,” in Proc. iCJ5SP 88 (New York, NY), 1988, E.6.5, pp. 2460- 2463.
Stainhaouer, Gregory; Bakamidis, Stelios; Dologlou, Ioannis, “Automatic Detection of Allergic Rhinitis in Patients”, International Conference on Computational Science and Computational Intelligence (CSCI), 5-7 Dec. 2019.
Tong, Renjie; Ye, Zhongfu, “Data fusion over localized sensor networks for parallel waveform enhancement based on 3-D tensor representations”, Signal Processing, Volume 141, December 2017, Pages 249-260.
Wang, Fasong; Wang, Zhongyong; Li, Rui; Zhang, Linrang “An efficient algorithm for harmonic retrieval by combining blind source separation with wavelet packet decomposition”, Digital Signal Processing, Volume 46, November 2015, pp. 133-150.