Eigenspectrum bounds for semirandom matrices with modular and spatial structure for neural networks

Dylan Muir, T. M. (2015). Eigenspectrum bounds for semirandom matrices with modular and spatial structure for neural networks.

Type

Unclassified

Intellectual base

Unclassified

Year

2015

DOI

10.1103/physreve.91.042808

Link

https://doi.org/10.1103/physreve.91.042808

Cited by

1 citation across 1 artifact.

Domain-specific

• Euclidean random matrix
  • … and a convenient observable transfers from A canonical example satisfies the full defining rule of Euclidean random matrix with all parameters and conventions explicit. to A careful use of Euclidean random matrix tests the constitutive rule, evidence and nearest confusable rather than relying on topical resemblance..

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