Neural gas is an artificial neural network, inspired by the self-organizing map and introduced in 1991 by Thomas Martinetz and Klaus Schulten.[1] The neural gas is a simple algorithm for finding optimal data representations based on feature vectors. The algorithm was coined "neural gas" because of the dynamics of the feature vectors during the adaptation process, which distribute themselves like a gas within the data space. It is applied where data compression or vector quantization is an issue, for example speech recognition,[2] image processing[3] or pattern recognition. As a robustly converging alternative to the k-means clustering it is also used for cluster analysis.[4]
^Thomas Martinetz and Klaus Schulten (1991). "A "neural gas" network learns topologies" (PDF). Artificial Neural Networks. Elsevier. pp. 397–402.
^F. Curatelli; O. Mayora-Iberra (2000). "Competitive learning methods for efficient Vector Quantizations in a speech recognition environment". In Osvaldo Cairó; L. Enrique Sucar; Francisco J. Cantú-Ortiz (eds.). MICAI 2000: Advances in artificial intelligence : Mexican International Conference on Artificial Intelligence, Acapulco, Mexico, April 2000 : proceedings. Springer. p. 109. ISBN 978-3-540-67354-5.
^Angelopoulou, Anastassia; Psarrou, Alexandra; Garcia Rodriguez, Jose; Revett, Kenneth (2005). "Computer Vision for Biomedical Image Applications". In Yanxi Liu; Tianzi Jiang; Changshui Zhang (eds.). Computer vision for biomedical image applications: first international workshop, CVBIA 2005, Beijing, China, October 21, 2005 : proceedings. Lecture Notes in Computer Science. Vol. 3765. Springer. p. 210. doi:10.1007/11569541_22. ISBN 978-3-540-29411-5.
^Fernando Canales; Max Chacon (2007). "Progress in Pattern Recognition, Image Analysis and Applications". In Luis Rueda; Domingo Mery (eds.). Progress in pattern recognition, image analysis and applications: 12th Iberoamerican Congress on Pattern Recognition, CIARP 2007, Viña del Mar-Valparaiso, Chile, November 13–16, 2007; proceedings. Lecture Notes in Computer Science. Vol. 4756. Springer. pp. 684–693. doi:10.1007/978-3-540-76725-1_71. ISBN 978-3-540-76724-4.
Neuralgas is an artificial neural network, inspired by the self-organizing map and introduced in 1991 by Thomas Martinetz and Klaus Schulten. The neural...
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Machine. Neural Networks, 24(8): 906-916, 2011 Jean-Charles Lamirel, Zied Boulila, Maha Ghribi, and Pascal Cuxac. A New Incremental Growing NeuralGas Algorithm...
kernel regression, artificial neural networks, support vector machines, mixture of experts, and supervised neuralgas. In addition, various metaheuristic...
algorithm (LBG) Learning vector quantization Lloyd's algorithm Growing NeuralGas, a neural network-like system for vector quantization Related topics Speech...
her Captain dies and frees Kirk, who neutralizes Khan's men by using a neuralgas. Khan heads to engineering and sets the ship's engines to self-destruct...
approach. It is a precursor to self-organizing maps (SOM) and related to neuralgas and the k-nearest neighbor algorithm (k-NN). LVQ was invented by Teuvo...
cluster and more weakly for inputs in other clusters. Ensemble learning Neuralgas Pandemonium architecture Rumelhart, David; David Zipser; James L. McClelland;...
A gas duster, also known as tinned wind or compressed air, is a product used for cleaning or dusting electronic equipment and other sensitive devices...
major contribution in the field of neuroinformatics is the so-called Neuralgas, a variant of self-organizing maps. He is co-founder of the software companies...
networks such as the growing neuralgas. Furthermore, it adds a noise reduction mechanism. There are several derived neural networks which extend TopoART...
conceivably survey an environment or detect explosives and gas. Similarly, DARPA is developing a neural implant to remotely control the movement of sharks. The...
Neuroplasticity, also known as neural plasticity or brain plasticity, is the ability of neural networks in the brain to change through growth and reorganization...
emergence, World Scientific, 2008 Ignazio Licata, Luigi Lella: Evolutionary neuralgas (ENG): A model of self rrganizing network from input categorization (2007)...
understand the fundamental and emergent properties of neurons, glia and neural circuits. The understanding of the biological basis of learning, memory...
Schulten. "A "neuralgas" network learns topologies" Artificial Neural Networks. Elsevier. pp. 397–402, 1991. B. Fritzke, "A growing neuralgas network learns...
"Generalization of backpropagation with application to a recurrent gas market model". Neural Networks. 1 (4): 339–356. doi:10.1016/0893-6080(88)90007-x. Sjöberg...
supervision where a small portion of the data is tagged, and Self Supervision. Neural network tasks are often categorized as discriminative (recognition) or generative...
occurred in our understanding of the neural processing of sounds in primates. Initially by recording of neural activity in the auditory cortices of monkeys...
learning, cellular neural networks (CNN) or cellular nonlinear networks (CNN) are a parallel computing paradigm similar to neural networks, with the difference...
cause altered ion permeability properties of the neural cells' lipid bilayers. The partial pressure of a gas required to cause a measured degree of impairment...
the University of Western Australia. Another example can be seen in the neurally controlled animat. The use of cultured neuronal networks as a model for...
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