Results 11 to 20 of about 96,569 (168)
Frontiers in Cellular Neuroscience, 2020 In the olfactory bulb, olfactory information is translated into ensemble representations by mitral/tufted cells, and these representations change dynamically in a context-dependent manner.
Dejuan Wang +6 more
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Hybrid Learning for General Type-2 TSK Fuzzy Logic Systems
Algorithms, 2017 This work is focused on creating fuzzy granular classification models based on general type-2 fuzzy logic systems when consequents are represented by interval type-2 TSK linear functions. Due to the complexity of general type-2 TSK fuzzy logic systems, a
Mauricio A. Sanchez +3 more
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A Granular Computing Based Classification Method From Algebraic Granule Structure
IEEE Access, 2021 Classification, as one of the main task of machine learning, corresponds to the core work of granular computing, namely granulation. Most of granular computing models and related classification methods are uniquely classifying by granule features, but ...
Linshu Chen +4 more
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Uncertainty Measurement for a Grey Information System
IEEE Access, 2019 A grey information system (GIS) is a new kind of IS. Uncertainty measurement (UM) can provide a new perspective for data analysis and help to reveal the essential features of data. This article studies UM for a GIS.
Zhihong Wang +4 more
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Cell Reports, 2020 Summary: Animals can store information about experiences by activating specific neuronal populations, and subsequent reactivation of these neural ensembles can lead to recall of salient experiences.
Sarah R. Erwin +5 more
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Towards Discovery of Information Granules [PDF]
, 1999 The amount of electronic data available is growing very fast and this explosive growth in databases has generated a need for new techniques and tools that can intelligently and automatically extract implicit, previously unknown, hidden and potentially useful information and knowledge from these data.
Andrzej Skowron, Jaroslaw Stepaniuk
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Spatiotemporal network coding of physiological mossy fiber inputs by the cerebellar granular layer. [PDF]
PLoS Computational Biology, 2017 The granular layer, which mainly consists of granule and Golgi cells, is the first stage of the cerebellar cortex and processes spatiotemporal information transmitted by mossy fiber inputs with a wide variety of firing patterns.
Shyam Kumar Sudhakar +8 more
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Local field potential modeling predicts dense activation in cerebellar granule cells clusters under LTP and LTD control. [PDF]
PLoS ONE, 2011 Local field-potentials (LFPs) are generated by neuronal ensembles and contain information about the activity of single neurons. Here, the LFPs of the cerebellar granular layer and their changes during long-term synaptic plasticity (LTP and LTD) were ...
Shyam Diwakar +4 more
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Neurobiology of Disease, 2021 Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by cognitive decline related to deficits in synaptic transmission and plasticity.
Nan Jiang +6 more
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Information granulation and granular relationships [PDF]
2005 IEEE International Conference on Granular Computing, 2005 As an emerging research method to deal with information and knowledge processing, various topics of granular computing have recently received more attention by researchers. The foundations of granular computing involves general principles of many disciplines that are explored for many years such as divide and conquer, interval computing, fuzzy sets ...
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