Title
Abstract geometrical computation 5: embedding computable analysis.
Abstract
Extended Signal machines are proven capable to compute any computable function in the understanding of recursive/computable analysis (CA), represented here with type-2 Turing machines (T2-TM) and signed binary. This relies on a mixed representation of any real number as an integer (in signed binary) plus an exact value in (−1, 1). This permits to have only finitely many signals present simultaneously. Extracting a (signed) bit, improving the precision by one bit and iterating a T2-TM only involve standard signal machines. For exact CA-computations, T2-TM have to deal with an infinite entry and to run through infinitely many iterations to produce an infinite output. This infinite duration can be provided by an infinite acceleration construction. Extracting/encoding an infinite sequence of bits is achieved as the limit of the approximation process with a careful handling of accumulations.
Year
DOI
Venue
2011
10.1007/s11047-010-9229-6
Natural Computing
Keywords
Field
DocType
Analog computation,Abstract geometrical computation,Computable analysis,Signal machine,Type-2 Turing machine
Sequence,Computer science,Artificial intelligence,Real number,Computable function,Recursion,Binary number,Discrete mathematics,Algorithm,Turing machine,Computable number,Machine learning,Computable analysis
Journal
Volume
Issue
ISSN
10
4
1567-7818
Citations 
PageRank 
References 
2
0.38
4
Authors
1
Name
Order
Citations
PageRank
Jérôme Durand-Lose112714.93