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Assembly of Cell‐Seeded 3D Printed Hydrogel Modules with Perfusable Channel Networks
Advanced Functional Materials, EarlyView.Macroscale assembly was utilized to prepare perfusable tissue constructs from individually 3D printed hydrogel modules with embedded branched channel networks and port arrays for cell seeding. Novel multi‐material bioreactors were fabricated to facilitate the gluing of individual modules and the perfusion culture of assembled modular constructs seeded ...
Zachary J. Geffert +10 more
wiley +1 more source
Advanced Functional Materials, EarlyView.Developing recyclable materials for magnetic robotics that combine rapid response and self‐healing properties is challenging. Hence, this study focuses on the integration of magnetothermal nanoparticles into a dynamic sorbitol‐based vitrimer, a recyclable composite capable of remote actuation and self‐healing by magnetic heating.
Maria Weißpflog +3 more
wiley +1 more source
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Asynchronous self-organizing maps
IEEE Transactions on Neural Networks, 2000A recently defined energy function which leads to a self-organizing map is used as a foundation for an asynchronous neural-network algorithm. We generalize the existing stochastic gradient approach to an asynchronous parallel stochastic gradient method for generating a topological map on a distributed computer system (MIMD).
M W, Benson, J, Hu
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Biological Cybernetics, 1989
Self-organized formation of topographic maps for abstract data, such as words, is demonstrated in this work. The semantic relationships in the data are reflected by their relative distances in the map. Two different simulations, both based on a neural network model that implements the algorithm of the selforganizing feature maps, are given.
Ritter, Helge, Kohonen, Teuvo
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Self-organized formation of topographic maps for abstract data, such as words, is demonstrated in this work. The semantic relationships in the data are reflected by their relative distances in the map. Two different simulations, both based on a neural network model that implements the algorithm of the selforganizing feature maps, are given.
Ritter, Helge, Kohonen, Teuvo
openaire +2 more sources
Recursive self-organizing maps
Neural Networks, 2002This paper explores the combination of self-organizing map (SOM) and feedback, in order to represent sequences of inputs. In general, neural networks with time-delayed feedback represent time implicitly, by combining current inputs and past activities.
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Self-organized criticality and the self-organizing map
Physical Review E, 2001The self-organizing map (SOM), a biologically inspired, learning algorithm from the field of artificial neural networks, is presented as a self-organized critical (SOC) model of the extremal dynamics family. The SOM's ability to converge to an ordered configuration, independent of the initial state, is known and has been demonstrated, in the one ...
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2013
Self-organizing maps are closely related to radial basis function networks. They can be seen as radial basis function networks without an output layer, or, rather, the hidden layer of a radial basis function network is already the output layer of a self-organizing map.
Rudolf Kruse +5 more
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Self-organizing maps are closely related to radial basis function networks. They can be seen as radial basis function networks without an output layer, or, rather, the hidden layer of a radial basis function network is already the output layer of a self-organizing map.
Rudolf Kruse +5 more
openaire +2 more sources
2011
This chapter introduces an approach for clustering and visualizing high-dimensional data, especially textual data. The self-organizing map (SOM) is a neural network paradigm for exploratory data analysis. The SOM is equipped with an unsupervised and competitive learning algorithm.
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This chapter introduces an approach for clustering and visualizing high-dimensional data, especially textual data. The self-organizing map (SOM) is a neural network paradigm for exploratory data analysis. The SOM is equipped with an unsupervised and competitive learning algorithm.
+4 more sources
Financial Self-Organizing Maps
2014This paper introduces Financial Self–Organizing Maps (FinSOM) as a SOM sub–class where the mapping of inputs on the neural space takes place using functions with economic soundness, that makes them particularly well–suited to analyze financial data. The visualization capabilities as well as the explicative power of both the standard SOM and the FinSOM ...
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2010
In PCA, the most outlying data points determine the direction of the PCs – these are the ones contributing most to the variance. This often results in score plots showing a large group of points close to the centre. As a result, any local structure is hard to recognize, even when zooming in: such points are not important in the determination of the PCs.
+4 more sources
In PCA, the most outlying data points determine the direction of the PCs – these are the ones contributing most to the variance. This often results in score plots showing a large group of points close to the centre. As a result, any local structure is hard to recognize, even when zooming in: such points are not important in the determination of the PCs.
+4 more sources