Literature DB >> 16566460

The parameterless self-organizing map algorithm.

Erik Berglund1, Joaquin Sitte.   

Abstract

The parameterless self-organizing map (PLSOM) is a new neural network algorithm based on the self-organizing map (SOM). It eliminates the need for a learning rate and annealing schemes for learning rate and neighborhood size. We discuss the relative performance of the PLSOM and the SOM and demonstrate some tasks in which the SOM fails but the PLSOM performs satisfactory. Finally we discuss some example applications of the PLSOM and present a proof of ordering under certain limited conditions.

Mesh:

Year:  2006        PMID: 16566460     DOI: 10.1109/TNN.2006.871720

Source DB:  PubMed          Journal:  IEEE Trans Neural Netw        ISSN: 1045-9227


  3 in total

1.  Data-driven automated acoustic analysis of human infant vocalizations using neural network tools.

Authors:  Anne S Warlaumont; D Kimbrough Oller; Eugene H Buder; Rick Dale; Robert Kozma
Journal:  J Acoust Soc Am       Date:  2010-04       Impact factor: 1.840

2.  Clustering Ensemble Model Based on Self-Organizing Map Network.

Authors:  Wenqi Hua; Lingfei Mo
Journal:  Comput Intell Neurosci       Date:  2020-08-25

3.  Pruning Growing Self-Organizing Map Network for Human Physical Activity Identification.

Authors:  Lingfei Mo; Hongjie Yu; Wenqi Hua
Journal:  J Healthc Eng       Date:  2022-01-03       Impact factor: 2.682

  3 in total

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