scholarly journals Total luminescence spectroscopy with pattern recognition for classification of edible oils

The Analyst ◽  
2003 ◽  
Vol 128 (7) ◽  
pp. 966 ◽  
Author(s):  
Simon M. Scott ◽  
David James ◽  
Zulfiqur Ali ◽  
William T. O'Hare ◽  
Fred. J. Rowell
Keyword(s):  
Pattern Recognition ◽  
Edible Oils ◽  
Luminescence Spectroscopy ◽  
Total Luminescence Spectroscopy

scholarly journals Discrimination of teas based on total luminescence spectroscopy and pattern recognition

2006 ◽  
Vol 86 (13) ◽  
pp. 2092-2098 ◽  
Author(s):  
L Nitin Seetohul ◽  
Meez Islam ◽  
William T O'Hare ◽  
Zulfiqur Ali
Keyword(s):  
Pattern Recognition ◽  
Luminescence Spectroscopy ◽  
Total Luminescence Spectroscopy

Characterization of Edible Oils Using Total Luminescence Spectroscopy

2004 ◽  
Vol 14 (1) ◽  
pp. 25-35 ◽  
Author(s):  
E. Sikorska ◽  
A. Romaniuk ◽  
I. V. Khmelinskii ◽  
R. Herance ◽  
J. L. Bourdelande ◽  
...  
Keyword(s):  
Edible Oils ◽  
Luminescence Spectroscopy ◽  
Total Luminescence Spectroscopy

scholarly journals Minimization of the Line Resistance Impact on Memdiode-Based Simulations of Multilayer Perceptron Arrays Applied to Pattern Recognition

2021 ◽  
Vol 11 (1) ◽  
pp. 9
Author(s):  
Fernando Leonel Aguirre ◽  
Nicolás M. Gomez ◽  
Sebastián Matías Pazos ◽  
Félix Palumbo ◽  
Jordi Suñé ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Ex Situ ◽  
Multilayer Perceptrons ◽  
Spice Simulation ◽  
Large Dataset ◽  
High Line ◽  
Calibration Algorithm ◽  
The Impact ◽  
Line Resistance

In this paper, we extend the application of the Quasi-Static Memdiode model to the realistic SPICE simulation of memristor-based single (SLPs) and multilayer perceptrons (MLPs) intended for large dataset pattern recognition. By considering ex-situ training and the classification of the hand-written characters of the MNIST database, we evaluate the degradation of the inference accuracy due to the interconnection resistances for MLPs involving up to three hidden neural layers. Two approaches to reduce the impact of the line resistance are considered and implemented in our simulations, they are the inclusion of an iterative calibration algorithm and the partitioning of the synaptic layers into smaller blocks. The obtained results indicate that MLPs are more sensitive to the line resistance effect than SLPs and that partitioning is the most effective way to minimize the impact of high line resistance values.

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