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Author Sanchez, P. ♦ Melin, P. ♦ Lopez, M.A.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2008
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Mobile robots ♦ Solids ♦ Neural networks ♦ Fuzzy logic ♦ Image recognition ♦ Feature extraction ♦ Mel frequency cepstral coefficient ♦ Optimization methods ♦ Image segmentation ♦ Computer vision
Abstract A hybrid system is a dynamical system with both discrete and continuous state changes such as those that combine neural networks and fuzzy logic. In this paper, we propose a method for voice and image recognition by implementing optimized neural networks and fuzzy logic to guide a distributed robot. Generally, word recognition systems are divided into three stages: segmentation, feature extraction and classification. We use a computer vision method for feature extraction, which is known as the Mel Frequency Cepstral Coefficients (MFCC). Genetic Algorithms (GA) are used for the optimization process in order to improve image recognition. The robot's world is a white square area measuring 2 square meters, the robot receives a voice request for a geometric solid and it must search between the different solids to find the one asked for. After this it must direct itself to the solid using a fuzzy guiding system.
Description Author affiliation: Div. of Res. & Grad. Studies, Tijuana Inst. of Technol., Tijuana (Sanchez, P.; Melin, P.; Lopez, M.A.)
ISBN 9781424423514
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2008-05-19
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 1.93 MB
Page Count 6
Starting Page 1
Ending Page 6

Source: IEEE Xplore Digital Library