Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The parity-check matrix of a linear code is used to define a bipartite code constraint (Tanner) graph in which bit nodes are connected to parity-check nodes. The connectivity properties of this graph are analyzed using both local connectivity and the eigenvalues of the associated adjacency matrix. A simple lor bound on the minimum distance of the code is expressed in terms of the two largest eigenvalues. For a more porful bound, local properties of the subgraph corresponding to a minimum-ight word in the code are used to create an optimization problem whose solution is a lor bound on the code's minimum distance. Linear programming gives one bound. The technique is illustrated by applying it to sparse block codes with parameters [7,3,4] and [42,23,6].
['Robert Michael Tanner']
I am writing a research paper on a idea Minimum-distance bounds by graph analysis
[{"from": "human", "value": "I am writing a research paper on a idea Minimum-distance bounds by graph analysis"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The parity-check matrix of a linear code is used to define a bipartite code constraint (Tanner) graph in which bit nodes are connected to parity-check nodes. The connectivity properties of this graph are analyzed using both local connectivity and the eigenvalues of the associated adjacency matrix. A simple lor bound on the minimum distance of the code is expressed in terms of the two largest eigenvalues. For a more porful bound, local properties of the subgraph corresponding to a minimum-ight word in the code are used to create an optimization problem whose solution is a lor bound on the code's minimum distance. Linear programming gives one bound. The technique is illustrated by applying it to sparse block codes with parameters [7,3,4] and [42,23,6]."}]