Neural gas is an artificial neural network, inspired by the self-organizing map and introduced in 1991 by Thomas Martinetz and Klaus Schulten. The neural...

In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a computational model inspired by the structure...

many types of artificial neural networks (ANN). Artificial neural networks are computational models inspired by biological neural networks, and are used...

major contribution in the field of neuroinformatics is the so-called Neural gas, a variant of self-organizing maps. He is co-founder of the software companies...

Physics-informed neural networks (PINNs), also referred to as Theory-Trained Neural Networks (TTNs), are a type of universal function approximators that...

kernel regression, artificial neural networks, support vector machines, mixture of experts, and supervised neural gas. In addition, various metaheuristic...

algorithm (LBG) Learning vector quantization Lloyd's algorithm Growing Neural Gas, a neural network-like system for vector quantization Related topics Speech...

approach. It is a precursor to self-organizing maps (SOM) and related to neural gas and the k-nearest neighbor algorithm (k-NN). LVQ was invented by Teuvo...

Machine. Neural Networks, 24(8): 906-916, 2011 Jean-Charles Lamirel, Zied Boulila, Maha Ghribi, and Pascal Cuxac. A New Incremental Growing Neural Gas Algorithm...

her Captain dies and frees Kirk, who neutralizes Khan's men by using a neural gas. Khan heads to engineering and sets the ship's engines to self-destruct...

self-organizing map Learning vector quantization Liquid state machine Neocognitron Neural gas Sparse coding Sparse distributed memory Topological data analysis Kohonen...

cluster and more weakly for inputs in other clusters. Ensemble learning Neural gas Pandemonium architecture Rumelhart, David; David Zipser; James L. McClelland;...

A gas duster, also known as tinned wind, compressed air, or canned air, is a product used for cleaning or dusting electronic equipment and other sensitive...

emergence, World Scientific, 2008 Ignazio Licata, Luigi Lella: Evolutionary neural gas (ENG): A model of self rrganizing network from input categorization (2007)...

networks such as the growing neural gas. Furthermore, it adds a noise reduction mechanism. There are several derived neural networks which extend TopoART...

Schulten. "A "neural gas" network learns topologies" Artificial Neural Networks. Elsevier. pp. 397–402, 1991. B. Fritzke, "A growing neural gas network learns...

conceivably survey an environment or detect explosives and gas. Similarly, DARPA is developing a neural implant to remotely control the movement of sharks. The...

Fuzzy Neural Networks (EFuNN) Evolving Self-Organising Maps neuro-fuzzy techniques hybrid intelligent systems fuzzy clustering Growing Neural Gas Lemaire...

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...

language models because they can usefully ingest large datasets. After neural networks became dominant in image processing around 2012, they were applied...

including search and mathematical optimization, formal logic, artificial neural networks, and methods based on statistics, operations research, and economics...

Neuroplasticity, also known as neural plasticity or just plasticity, is the ability of neural networks in the brain to change through growth and reorganization...

understand the fundamental and emergent properties of neurons, glia and neural circuits. The understanding of the biological basis of learning, memory...

automated targeted analysis of raw gas chromatography-mass spectrometry data". 2018 International Joint Conference on Neural Networks (IJCNN). pp. 1–8. doi:10...

learning, cellular neural networks (CNN) or cellular nonlinear networks (CNN) are a parallel computing paradigm similar to neural networks, with the difference...

recurrent neural networks, such as Elman networks. The algorithm was independently derived by numerous researchers. The training data for a recurrent neural network...

include Kalman filters. More recent implementations of soft sensors use neural networks or fuzzy computing. Examples of soft sensor applications: Kalman...

large-scale unsupervised learning have been done by training general-purpose neural network architectures by gradient descent, adapted to performing unsupervised...

analysis of gravitational orbits, ensemble forecasting of weather, dynamics of neural networks, bounded-rational potential games in game theory and non-equilibrium...

aerobullosis, and caisson disease) is a medical condition caused by dissolved gases emerging from solution as bubbles inside the body tissues during decompression...