K
Katherine Morrison
Researcher at University of Northern Colorado
Publications - 36
Citations - 587
Katherine Morrison is an academic researcher from University of Northern Colorado. The author has contributed to research in topics: Fixed point & Error detection and correction. The author has an hindex of 12, co-authored 33 publications receiving 474 citations. Previous affiliations of Katherine Morrison include University of Nebraska–Lincoln & Pennsylvania State University.
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Equivalence for Rank-Metric and Matrix Codes and Automorphism Groups of Gabidulin Codes
TL;DR: In this article, a framework for classifying rank-metric and matrix codes based on their structure and distance properties has been proposed, and the set of equivalence maps that fix the prominent class of Gabidulin codes known as rank-matric codes has been characterized.
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What Makes a Neural Code Convex
Carina Curto,Elizabeth Gross,Jack Jeffries,Katherine Morrison,Mohamed Omar,Zvi Rosen,Zvi Rosen,Anne Shiu,Nora Youngs +8 more
TL;DR: This work provides a complete characterization of local obstructions to convexity and defines max intersection-complete codes, a family guaranteed to have noLocal obstructions, a significant advance in understanding the intrinsic combinatorial properties of convex codes.
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Cyclic Orbit Codes and Stabilizer Subfields
TL;DR: In this article, the cardinality of the cyclic subspace codes is determined using the largest subfield over which the given subspace is a vector space, and estimates for its distance can be found.
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What makes a neural code convex
Carina Curto,Elizabeth Gross,Jack Jeffries,Katherine Morrison,Mohamed Omar,Zvi Rosen,Zvi Rosen,Anne Shiu,Nora Youngs +8 more
TL;DR: In this paper, the authors provide a complete characterization of local obstructions to convexity and define max intersection-complete codes, a family of convex codes with no local obstruction.
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Combinatorial neural codes from a mathematical coding theory perspective
TL;DR: It is suggested that a compromise in error-correcting capability may be a necessary price to pay for a neural code whose structure serves not only error correction, but must also reflect relationships between stimuli.