DocumentCode
1815171
Title
Two neuron CNN for hypothesis testing
Author
Vinyoles-Serra, Mireia ; Vilasís-Cardona, Xavier
Author_Institution
LIFAELS, Univ. Ramom Llull, Barcelona, Spain
fYear
2012
fDate
29-31 Aug. 2012
Firstpage
1
Lastpage
6
Abstract
The two neuron continues time cellular neural network is used to define a statistic in the classical hypothesis testing problem. The proposal is based on a generalisation of the linear Fisher discriminant. The procedure to set the cellular neural network parameters is described and the performance shown on two examples with gaussianly distributed hypothesis. This technique might also be applied to probabilistic classification problems or pattern recognition.
Keywords
Gaussian distribution; cellular neural nets; generalisation (artificial intelligence); pattern classification; statistical analysis; Gaussianly distributed hypothesis; cellular neural network parameters; hypothesis testing problem; linear Fisher discriminant generalisation; pattern recognition; probabilistic classification problems; two neuron CNN; two neuron continous time cellular neural network; Cellular neural networks; Convergence; Distributed databases; Neurons; Probability; Testing; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Nanoscale Networks and Their Applications (CNNA), 2012 13th International Workshop on
Conference_Location
Turin
ISSN
2165-0160
Print_ISBN
978-1-4673-0287-6
Type
conf
DOI
10.1109/CNNA.2012.6331424
Filename
6331424
Link To Document