Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 6 of 6 for “"recurrent connectivity"”.
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Lateralized Temporal Integration Properties of the Mouse Auditory Cortex
… capable of processing these signals is through recurrent connectivity in the cortical circuits. Recurrent connectivity is proposed to be a possible circuit motif that aids in the processing of these transient signals. Recurrent connectivity is believed to have an effect on the temporal fidelity, …
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Biologically inspired feature extraction for rotation and scale tolerant pattern analysis
… and more generally, linear networks with recurrent connectivity along with complex-log conformal mapping in machine based implementations of information encoding, feature extraction and pattern recognition. The reasoning behind and method for spatially uniform implementation of …
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Evolutionary Design of Artificial Neural Networks Using a Descriptive Encoding Language
… this approach is shown to work for encoding recurrent neural networks for a temporal sequence generation problem, and the trade-offs between various recurrent network architectures are systematically compared via multi-objective optimization. Finally, it is shown that this system can be …
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Dynamic speech networks in the brain: Dual contribution of incrementality and constraints in access to semantics
… local syntactic ambiguities. The analysis of the connectivity dynamics in the left frontotemporal syntax network showed that the processing of sentences that contained the less anticipated syntactic structure showed early increased feedforward information flow in 0-100 ms, followed by increased …
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Inference and Learning in Spiking Neural Networks for Neuromorphic Systems
… Long Short-Term Memory (LSTM), a version of recurrent neural network (RNN) which includes recurrent connectivity to enable learning long temporal patterns. This is specifically a difficult challenge due to the inherent nature of RNNs and SNNs; the recurrent connectivity in RNNs induces …
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Inference And Learning In Spiking Neural Networks For Neuromorphic Systems
… Long Short-Term Memory (LSTM), a version of recurrent neural network (RNN) which includes recurrent connectivity to enable learning long temporal patterns. This is specifically a difficult challenge due to the inherent nature of RNNs and SNNs; the recurrent connectivity in RNNs induces …