Nonlinear Method of Reduction of Dimensionality Based on Artificial Neural Network and Hardware Implementation

2015 ◽  
pp. 69-79
Author(s):  
J. R. G. Braga ◽  
V. C. Gomes ◽  
E. H. Shiguemori ◽  
H. F. C. Velho ◽  
A. Plaza ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Hardware Implementation ◽  
Nonlinear Method ◽  
Reduction Of Dimensionality ◽  
Artificial Neural

Test on Flood Prediction-Model Using Artificial Neural Network for ShiiLiAn Hydrologic Station on MinChiang,China

2010 ◽  
Vol 39 ◽  
pp. 555-561 ◽  
Author(s):  
Qing Hua Luan ◽  
Yao Cheng ◽  
Zha Xin Ima
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Flood Control ◽  
Back Propagation ◽  
Forecast Model ◽  
Flood Forecast ◽  
Back Propagation Algorithm ◽  
Nonlinear Method ◽  
Flood Prediction ◽  
Artificial Neural

The establishing of a precise simulation model for runoff prediction in river with several tributaries is the difficulty of flood forecast, which is also one of the difficulties in hydrologic research. Due to the theory of Artificial Neural Network, using Back Propagation algorithm, the flood forecast model for ShiLiAn hydrologic station in Minjiang River is constructed and validated in this study. Through test, the result shows that the forecast accuracy is satisfied for all check standards of flood forecast and then proves the feasibility of using nonlinear method for flood forecast. This study provides a new method and reference for flood control and water resources management in the local region.

scholarly journals Design of an OCR System and its Hardware Implementation

2021 ◽  
Vol 9 (12) ◽  
pp. 159-174
Author(s):  
Gulfeshan Parween
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Character Recognition ◽  
Hardware Implementation ◽  
Gray Level ◽  
Document Images ◽  
English Alphabet ◽  
Barcode Recognition ◽  
Printed Text ◽  
Artificial Neural

Abstract: In this paper, we present a scheme to develop to complete OCR system for printed text English Alphabet of Uppercase of different font and of different sizes so that we can use this system in Banking, Corporate, Legal industry and so on. OCR system consists of different modules like preprocessing, segmentation, feature extraction and recognition. In preprocessing step it is expected to include image gray level conversion, binary conversion etc. After finding out the feature of the segmented characters artificial neural network and can be used for Character Recognition purpose. Efforts have been made to improve the performance of character recognition using artificial neural network techniques. The proposed OCR system is capable of accepting printed document images from a file and implemented using MATLAB R2014a version. Key words: OCR, Printed text, Barcode recognition

Sign in / Sign up

Export Citation Format

Share Document