Title :
Large-neighborhood templates implementation in discrete-time CNN Universal Machine with a nearest-neighbor connection pattern
Author_Institution :
Inst. of Electron., Tech. Univ. Lodz, Poland
Abstract :
The paper presents the method of large neighborhood templates realization (i.e. templates with r>1) in a nearest-neighbor connected (i.e. r=1) discrete-time CNN Universal Machine. This is accomplished by decomposing an objective template into a sum of two-dimensional 3×3 template correlations. An appropriate procedure which ensures a desired circuit operation is given in an algorithmic form
Keywords :
Turing machines; cellular neural nets; discrete time systems; image processing; parallel machines; 2D 3×3 template correlations; algorithmic form; circuit operation; large-neighborhood templates implementation; nearest-neighbor connected discrete-time CNN Universal Machine; nearest-neighbor connection pattern; objective template decomposition; Analog computers; Cellular neural networks; Circuits; Computer networks; Concurrent computing; Matrix decomposition; Parallel processing; Signal processing algorithms; Turing machines; Very large scale integration;
Conference_Titel :
Cellular Neural Networks and their Applications, 1994. CNNA-94., Proceedings of the Third IEEE International Workshop on
Conference_Location :
Rome
Print_ISBN :
0-7803-2070-0
DOI :
10.1109/CNNA.1994.381677
