Title
Index Generation Functions Based on Linear and Polynomial Transformations
Abstract
Index generation functions are a particular class ofswitching (Boolean or multiple-valued) functions that have some important applications in communication, data retrieval and processing, and related areas. For these applications, determining compact representations of index generation functions is an important task. An approach towards this is to perform a linear transformation to reduce the number of required variables, but finding an optimal transformation can be difficult. In this paper, we propose non-linear transformations to reduce the number of variables, and formulate the problem of finding a good linear transformation using linear subspaces. Extendingthe set of initial variables by products of variables makes iteasier to find a compact representation as the number of suitable transformations becomes larger.
Year
DOI
Venue
2016
10.1109/ISMVL.2016.20
2016 IEEE 46th International Symposium on Multiple-Valued Logic (ISMVL)
Keywords
Field
DocType
index generation functions,linear transformation,polynomial transformation,linear spaces
Signal processing,Discrete mathematics,Polynomial transformation,Markov process,Polynomial,Data retrieval,Computer science,Linear subspace,Linear map,Linear predictor function
Conference
ISSN
ISBN
Citations 
0195-623X
978-1-4673-9490-1
3
PageRank 
References 
Authors
0.41
12
3
Name
Order
Citations
PageRank
Helena Astola182.98
Radomir S. Stankovic218847.07
Jaakko Astola31515230.41