Embedding multiple trajectories in recurrent neural networks in a self-organizing manner
نویسندگان
چکیده
منابع مشابه
Embedding multiple trajectories in simulated recurrent neural networks in a self-organizing manner.
Complex neural dynamics produced by the recurrent architecture of neocortical circuits is critical to the cortex's computational power. However, the synaptic learning rules underlying the creation of stable propagation and reproducible neural trajectories within recurrent networks are not understood. Here, we examined synaptic learning rules with the goal of creating recurrent networks in which...
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شبکه خود سازمانده پرکاربردترین شبکه عصبی برای انجام خوشه بندی و کوانتیزه نمودن برداری است. از زمان معرفی این شبکه تاکنون، از این روش در مسائل مختلف در حوزه های گوناگون استفاده و توسعه ها و بهبودهای متعددی برای آن ارائه شده است. شبکه خودسازمانده از تعدادی سلول برای تخمین تابع توزیع الگوهای ورودی در فضای چندبعدی استفاده می کند. احتمال وجود سلول مرده مشکلی اساسی در الگوریتم شبکه خودسازمانده به حسا...
A Self-organizing Recurrent Neural Network
A recurrent neural network with a self-organizing structure based on the dynamic analysis of a task is presented in this paper. The stability of the recurrent neural network is guaranteed by design. A dynamic analysis method to sequence the subsystems of the recurrent neural network according to the fitness between the subsystems and the target system is developed. The network is trained with t...
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Understanding the dynamics of recurrent neural networks is crucial for explaining how the brain processes information. In the neocortex, a range of different plasticity mechanisms are shaping recurrent networks into effective information processing circuits that learn appropriate representations for time-varying sensory stimuli. However, it has been difficult to mimic these abilities in artific...
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Due to large datavolumes when remote sensing or other kind of images are used, there is need for methods to decrease the volume of data. Methods for decreasing the feature dimension, in other words number of channels, are called feature selection and feature extraction. In the feature selection, important channels are selected using some search technique and these channels are used for current ...
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ژورنال
عنوان ژورنال: Frontiers in Systems Neuroscience
سال: 2009
ISSN: 1662-5137
DOI: 10.3389/conf.neuro.06.2009.03.315