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Using Sinusoidally-Modulated Noise as a Surrogate for Slow-Wave Sleep to Accomplish Stable Unsupervised Dictionary Learning in a Spike-Based Sparse Coding Model

机译:使用正弦调制的噪声作为慢波睡眠的替代品,在基于峰值的稀疏编码模型中完成稳定的无监督词典学习

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Sparse coding algorithms have been used to model the acquisition of V1 simple cell receptive fields as well as to accomplish the unsupervised acquisition of features for a variety of machine learning applications. The Locally Competitive Algorithm (LCA) p
机译:稀疏编码算法已用于对V1简单单元格接收场的获取进行建模,以及完成针对各种机器学习应用程序的无监督特征获取。本地竞争算法(LCA)p

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