S. N. Sivanandam,. Professor Dynamic neural networks are good at time series prediction. Elman neural model being recurrent neural network, architecture. From my experience of yesterday when I was preparing for my presentation, I have a topic on Artificial Neural network tell me the properties of Artifi. S. N. Sivanandam, S. Sumathi and S. N. Deepa, “Introduction to Neural Networks using Matlab ,” Tata McGraw-Hill, New Delhi,
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A data acquisition system based on National Instruments NI software and hardware was developed for robot vibration analysis and feature extraction.
- Introduction to Fuzzy Logic using MATLAB - S.N. Sivanandam, S. Sumathi, S. N. Deepa - Google Books
- Introduction to neural networks using MATLAB 6.0 /
- 9780070591127 - Introduction To Neural Networks With Matlab 6.0, 1Ed by SIVANANDAM S N
An experimental investigation was accomplished using the PUMA robot. Firstly, vibration signals are captured from the robot when it is moving one joint cyclically. Then, by utilising the wavelet transform, signals are decomposed into multi-band frequency levels starting sivanandam neural networks higher to lower frequencies.
For each of these levels the standard deviation feature is computed and used to design, train and test the proposed neural network. The developed system has showed high reliability in diagnosing several seeded backlash levels in sivanandam neural networks robot.
Introduction to neural networks using MATLAB (Book, ) 
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S Sivanandam (Author of Introduction to Neural Networks With Mat)
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