Memory Capacity of Neural Networks using a Circulant Weight Matrix

📝 Original Info

• Title: Memory Capacity of Neural Networks using a Circulant Weight Matrix
• ArXiv ID: 1403.3115
• Date: 2014-03-14
• Authors: Researchers from original ArXiv paper

📝 Abstract

This paper presents results on the memory capacity of a generalized feedback neural network using a circulant matrix. Children are capable of learning soon after birth which indicates that the neural networks of the brain have prior learnt capacity that is a consequence of the regular structures in the brain's organization. Motivated by this idea, we consider the capacity of circulant matrices as weight matrices in a feedback network.

💡 Deep Analysis

Deep Dive into Memory Capacity of Neural Networks using a Circulant Weight Matrix.

This paper presents results on the memory capacity of a generalized feedback neural network using a circulant matrix. Children are capable of learning soon after birth which indicates that the neural networks of the brain have prior learnt capacity that is a consequence of the regular structures in the brain’s organization. Motivated by this idea, we consider the capacity of circulant matrices as weight matrices in a feedback network.

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