Title :
Two neuron CNN for hypothesis testing
Author :
Vinyoles-Serra, Mireia ; Vilasís-Cardona, Xavier
Author_Institution :
LIFAELS, Univ. Ramom Llull, Barcelona, Spain
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;
Conference_Titel :
Cellular Nanoscale Networks and Their Applications (CNNA), 2012 13th International Workshop on
Conference_Location :
Turin
Print_ISBN :
978-1-4673-0287-6
DOI :
10.1109/CNNA.2012.6331424
