The parameterless self-organizing map algorithm
Erik Berglund,Joaquin Sitte +1 more
TL;DR: The relative performance of the PLSOM and the SOM is discussed and some tasks in which the SOM fails but the P LSOM performs satisfactory are demonstrated and a proof of ordering under certain limited conditions is presented.
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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.
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Citations
Homogeneity versus heterogeneity of cultural values: An item-response theoretical approach applying Hofstede's cultural dimensions in a single nation
TL;DR: In this article, the authors tested the validity and reliability of a scale designed to measure Hofstede's five cultural dimensions at the individual or psychological level across two large ( n Â>500) convenience samples of the United States population.
62
Denoising Autoencoder Self-Organizing Map (DASOM).
TL;DR: The Denoising Autoencoder Self-Organizing Map (DASOM) is presented that integrates the latter into a hierarchically organized hybrid model where the front-end component is a grid of topologically ordered neurons.
53
Topology-oriented self-organizing maps: a survey
TL;DR: The overall goal of this survey is to present a comprehensive comparison of these networks, in terms of their primitive components and properties, and dichotomize these schemes as being either tree based or non-tree based.
48
Self-Organizing and Self-Evolving Neurons: A New Neural Network for Optimization
Sitao Wu,Tommy W. S. Chow +1 more
TL;DR: At last, the computational time of parallel SOSENs can be less than the SA, and every neuron exhibits a self-organizing behavior, which is similar to those of the self- Organizing map (SOM), particle swarm optimization (PSO), and self-Organizing migrating algorithm (SomA).
Sound source localisation through active audition
Erik Berglund,Joaquin Sitte +1 more
- 01 Jan 2005
TL;DR: A new neural network, the parameter-less self-organizing map algorithm, and reinforcement learning are used to achieve rapid and accurate response to determine the direction to a sound source through interacting with its environment.
42
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