Fuzzy multi-layer perceptron for binary pattern recognition

1999 ◽  
Author(s):  
A.M.P. Canuto
Keyword(s):  
Pattern Recognition ◽  
Multi Layer Perceptron

Multi-Layer Perceptron Pattern Recognition of Handwriting Ink Based on PLS-DA Raman Spectral Feature Extraction

2021 ◽  
Vol 58 (1) ◽  
pp. 0130002
Author(s):  
王晓宾 Wang Xiaobin ◽  
马枭 Ma Xiao ◽  
杨蕾 Yang Lei ◽  
李春宇 Li Chunyu
Keyword(s):  
Pattern Recognition ◽  
Feature Extraction ◽  
Spectral Feature ◽  
Multi Layer Perceptron ◽  
Raman Spectral

scholarly journals Multi layer perceptron model in pattern recognition of surface parameters during pre-monsoon thunderstorm

MAUSAM ◽  
2022 ◽  
Vol 53 (4) ◽  
pp. 417-424
Author(s):  
SUTAPA CHAUDHURI ◽  
SURAJIT CHATTOPADHYAY
Keyword(s):  
Pattern Recognition ◽  
Fuzzy Logic ◽  
Surface Temperature ◽  
Surface Pressure ◽  
Dew Point ◽  
Multi Layer Perceptron ◽  
Surface Parameters ◽  
Point Temperature ◽  
Dew Point Temperature ◽  
Definite Pattern

The concept of Multi Layer Perceptron and Fuzzy logic is introduced in this paper to recognize the pattern of surface parameters pertaining to forecast the occurrence of pre-monsoon thunderstorms over Kolkata (22 ° 32¢ , 88 ° 20¢ ).   The results reveal that surface temperature fluctuates significantly from Fuzzy Multi Layer Perceptron (FMLP) model values on thunderstorm days whereas on non-thunderstorm days FMLP model fits well with the surface temperature.   The results further indicate that no definite pattern could be made available with surface dew point temperature and surface pressure that can help in forecasting the occurrence of these storms.

Adaptive Network Structures for Data/Text Pattern Recognition (Application)

2013 ◽  
pp. 280-294
Author(s):  
Emmanuel Buabin
Keyword(s):  
Neural Networks ◽  
Pattern Recognition ◽  
Real World ◽  
Recurrent Neural Networks ◽  
Intelligent Systems ◽  
Classification Systems ◽  
Multi Layer Perceptron ◽  
Is Implementation ◽  
Processing Techniques

The objective of this chapter is implementation of neural based solutions in real world context. In particular, a step-wise approach to constructing, training, validating, and testing of selected feed-forward (Multi-Layer Perceptron, Radial Basis function) and recurrent (Recurrent Neural Networks) neural based classification systems are demonstrated. The pre-processing techniques adopted in extracting information from selected datasets are also discussed. In terms of future practical directions, a catalogue of intelligent systems across selected disciplines, are outlined. The main contribution of this book chapter is to provide basic introductory text with less mathematical rigor for the benefit of students, tutors, lecturers, researchers, and/or professionals who wish to delve into foundational (practical) representations of bio-intelligent intelligent systems.

Line Resistance Impact in Memristor-based Multi Layer Perceptron for Pattern Recognition

2021 ◽  
Author(s):  
F. L. Aguirre ◽  
S. M. Pazos ◽  
F. Palumbo ◽  
N. Gomez ◽  
E. Miranda ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Multi Layer Perceptron ◽  
Line Resistance
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