caa a22 4500 475800834 CHVBK 20180406123736.0 cr unu---uuuuu 170329e20001201xx s 000 0 eng 10.1023/A:1026532632696 doi (NATIONALLICENCE)springer-10.1023/A:1026532632696 Self-Organization by Temporal Inhibition (SOTI) [Elektronische Daten] [P. Martín-Smith, F. Pelayo, E. Ros, A. Prieto] A model is presented for a neural network with competitive learning that demonstrates the self-organizing capabilities arising from the inclusion of a simple temporal inhibition mechanism within the neural units. This mechanism consists of the inhibition, for a certain time, of the neuron that generates an action potential; such a process is termed Post_Fire inhibition. The neural inhibition period, or degree of inhibition, and the way it is varied during the learning process, represents a decisive factor in the behaviour of the network, in addition to constituting the main basis for the exploitation of the model. Specifically, we show how Post_Fire inhibition is a simple mechanism that promotes the participation of and cooperation between the units comprising the network; it produces self-organized neural responses that reveal spatio-temporal characteristics of input data. Analysis of the inherent properties of the Post_Fire inhibition and the examples presented show its potential for applications such as vector quantization, clustering, pattern recognition, feature extraction and object segmentation. Finally, it should be noted that the Post_Fire inhibition mechanism is treated here as an efficient abstraction of biologically plausible mechanisms, which simplifies its implementation. Kluwer Academic Publishers, 2000 temporal inhibition nationallicence competitive learning nationallicence self-organizing maps nationallicence learning vector quantization nationallicence Martín-Smith P. Departamento de Arquitectura y Tecnología de Computadores, University of Granada, Spain aut Pelayo F. Departamento de Arquitectura y Tecnología de Computadores, University of Granada, Spain aut Ros E. Departamento de Arquitectura y Tecnología de Computadores, University of Granada, Spain aut Prieto A. Departamento de Arquitectura y Tecnología de Computadores, University of Granada, Spain aut Neural Processing Letters Kluwer Academic Publishers 12/3(2000-12-01), 199-213 1370-4621 12:3<199 2000 12 11063 https://doi.org/10.1023/A:1026532632696 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1023/A:1026532632696 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Martín-Smith P. Departamento de Arquitectura y Tecnología de Computadores, University of Granada, Spain aut NATIONALLICENCE 700 1- Pelayo F. Departamento de Arquitectura y Tecnología de Computadores, University of Granada, Spain aut NATIONALLICENCE 700 1- Ros E. Departamento de Arquitectura y Tecnología de Computadores, University of Granada, Spain aut NATIONALLICENCE 700 1- Prieto A. Departamento de Arquitectura y Tecnología de Computadores, University of Granada, Spain aut NATIONALLICENCE 773 0- Neural Processing Letters Kluwer Academic Publishers 12/3(2000-12-01), 199-213 1370-4621 12:3<199 2000 12 11063 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer