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The functional hyperactivity may be evidence for a dysfunctional encoding mechanism, consistent with the predictions of computational models of hippocampal learning.
To improve the effectiveness of current algorithms on MLRAP, this paper proposes a hybrid genetic algorithm (HGA) based on the two dimensional redundancy encoding mechanism.
We design the new encoding mechanism with a multi-functional chromosome that uses the priority representation the so-called priority-based multi-chromosome (PMC).
In this work, we present an encoding mechanism that reduces switching activity of external address buses by combining a memory reference caching mechanism with Unit Distance Redundant Codes (UDRC).
A modified multi-objective artificial bee colony (MOABC) algorithm is introduced to solve the MDCSCN model, which integrates the priority-based encoding mechanism, the Pareto optimality and the swarm intelligence of the bee colony.
Here we present a large-scale model of a hierarchical spiking neural network (SNN) that integrates a low-level memory encoding mechanism with a higher-level decision process to perform a visual classification task in real-time.
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We found evidence for dissociative neurocognitive encoding mechanisms supporting subsequent-recall and subsequent-recognition.
We seek to learn auditory representations of intermediate complexity, to better understand the structure of sound and to generate hypotheses about neural encoding mechanisms.
Covers in depth the physics of image encoding, mechanisms of anatomical and functional contrasts, the physiological basis of fMRI signals, cerebral hemodynamics, and neurovascular coupling.
Specifically, we propose reliable out-of-order transmission and bursty encoding mechanisms to transmit packets as many as possible in each transmission slot.
Encoding mechanisms invariably adapt or associate fresh data to information already present, to such an extent that what is encoded may not be a direct representation of incoming stimuli.
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