On the Gap between Scalar and Vector Solutions of Generalized Combination Networks

01/13/2020
by   Hedongliang Liu, et al.
0

We study scalar-linear and vector-linear solutions to the generalized combination network. We derive new upper and lower bounds on the maximum number of nodes in the middle layer, depending on the network parameters. These bounds improve and extend the parameter range of known bounds. Using these new bounds we present a general lower bound on the gap in the alphabet size between scalar-linear and vector-linear solutions.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/19/2022

Covering Grassmannian Codes: Bounds and Constructions

Grassmannian 𝒢_q(n,k) is the set of all k-dimensional subspaces of the v...
research
01/04/2019

Network Coding Solutions for the Combination Network and its Subgraphs

The combination network is one of the simplest and insightful networks i...
research
01/08/2018

Grassmannian Codes with New Distance Measures for Network Coding

Subspace codes are known to be useful in error-correction for random net...
research
03/17/2021

Lower Bounds on the Size of General Branch-and-Bound Trees

A general branch-and-bound tree is a branch-and-bound tree which is allo...
research
06/01/2022

Lower and Upper Bounds for Numbers of Linear Regions of Graph Convolutional Networks

The research for characterizing GNN expressiveness attracts much attenti...
research
01/09/2019

Generalized Deduplication: Bounds, Convergence, and Asymptotic Properties

We study a generalization of deduplication, which enables lossless dedup...
research
08/10/2021

Scalar actions in Lean's mathlib

Scalar actions are ubiquitous in mathematics, and therefore it is valuab...

Please sign up or login with your details

Forgot password? Click here to reset