Aimin Zhou, Qingfu Zhang, Yaochu Jin, Bernhard Sendhoff, Edward Tsang,
"Global multi-objective optimization via estimation of distribution algorithm with biased initialization and crossover",
Genetic and Evolutionary Computation Conference, 2007.
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Xavier Domont, Martin Heckmann, Heiko Wersing, Frank Joublin, Christian Goerick,
"A Hierarchical Model for Syllable Recognition",
European Symposium on Artificial Neural Networks (ESANN), pp. 573–578, 2007.
Abstract
Inspired by recent findings on the similarities between the primary auditory and visual cortex we propose a neural network for speech recognition based on a hierarchical feedforward architecture for visual object recognition. When using a Gammatone filterbank for the spectral analysis the resulting spectrograms of syllables can be interpreted as images. After a preprocessing enhancing the formants in the speech signal and a length normalization, ...
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Jochen Eppler, Hans Plesser, Abigail Morrison, Markus Diesmann, Marc-Oliver Gewaltig,
"Multithreaded and Distributed Simulation of Large Biological Neuronal Networks",
Recent Advances in Parallel Virtual Machine and Message Passing Interface, issue Volume 4757/2007, pp. 391-392, 2007.
Abstract
To understand the principles of information processing in the brain, we depend on models with more than 10^5 neurons and 10^9 connections. These networks can be described as graphs of threshold elements that exchange point events....
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Jochen Steil, Michael Götting, Heiko Wersing, Edgar Körner, Helge Ritter,
"Adaptive Scene-Dependent Filters for Segmentation and Online Learning of Visual Objects",
Neurocomputing, vol. 70, pp. 1235–1246, 2007.
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Sven Rebhan, Julian Eggert, Horst-Michael Groß, Edgar Körner,
"Sparse and Transformation-Invariant Hierarchical NMF",
Artificial Neural Networks, 17 th International Conference (ICANN), pp. 894–903, 2007.
Abstract
The hierarchical non-negative matrix factorization (HNMF) is a multilayer generative network for decomposing strictly positive data into strictly positive activations and base vectors in a hierarchical manner. However, the standard hierarchical NMF is not suited for overcomplete representations and does not code efficiently for transformations in the input data. Therefore we extend the standard HNMF by sparsity conditions and transformation-invar...
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Rüdiger Kupper, Andreas Knoblauch, Marc-Oliver Gewaltig, Ursula Körner, Edgar Körner,
"Simulations of signal flow in a functional model of the cortical column",
Neurocomputing, vol. 70, no. 10-12, pp. 1711-1716, 2007.
Abstract
We describe the simulation of a layered cortex model based on the cortical column as a generic local processor. It simulates the signal flow in the layers I–IV of a set of model columns across three hierarchical cortical areas. It demonstrates the fast formation of an initial stimulus hypothesis, and its subsequent refinement by inter-columnar communication. In this prototype simulation, we implement word recognition from a string of characters...
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Lars Gräning, Markus Olhofer, Bernhard Sendhoff,
"Knowledge Extraction from Unstructured Surface Meshes",
Proceedings of the 8th International Conference on Intelligent Data Egineering and Automated Learning (IDEAL), pp. 497–506, 2007.
Abstract
We propose methods that allow the investigation of local modifications of aerodynamic design data represented by discrete unstructured surface meshes. A displacement measure is suggested to evaluate local differences between the shapes. The displacement measure provides information on the amount and direction of surface modifications. Using the displacement measure in conjunction with statistical methods or data mining techniques provides meaning...
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Lars Gräning, Yaochu Jin, Bernhard Sendhoff,
"Individual-based management of meta-models for evolutionary optimization with applications to three-dimensional blade optimization",
Evolutionary Computation in Dynamic and Uncertain Environments, Springer, 2007.
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Rüdiger Kupper, Andreas Knoblauch, Ursula Körner, Edgar Körner, Marc-Oliver Gewaltig,
"Fast visual responses: Is counting spikes enough?",
Cosyne 2007, 4th Computational and Systems, Salt Lake City, Utah, USA, pp. 189, 2007.
Abstract
In visual processing, the cortex very quickly arrives at a hypothesis about the stimulus [1]. Thorpe et al. suggested, that this hypothesis is generated in a feed-forward network, where each feature-selective cell evaluates the order (rank) of incoming spikes [2]. However, to evaluate a rank code, every feature-selective neuron needs a local readout circuit. This is both biologically implausible and expensive to implement. We propose, that post-s...
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Hans-Georg Beyer and Bernhard Sendhoff,
"Evolutionary Algorithms in the Presence of Noise - To sample or not to sample",
IEEE Symposium on Foundations of Computational Intelligence, FOCI, 2007.
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