Learn More
  • Design—Martin T. Hagan, Howard B. Demuth
  • 1997
This book gives an introduction to basic neural-network architec-tures and their learning rules. It emphasizes mathematical analysis of the networks and their learning algorithms as well as their application to practical engineering problems in such areas as pattern recognition, signal processing, and control systems, The material is presented with(More)
I. INTRODUCTION. Artificial neural network (ANN) model have an ability to recognize time series patterns and nonlinear optimization and training algorithm optimization (Hagan et al., 1996). As shown in Neural Network Design. 1st Edn. De Jes s NEURAL NETWORK DESIGN (2nd Edition) provides a clear and detailed A free 1012 page eBook version of the book (11.4(More)
This work presents the implementation of trainable Artificial Neural Network (ANN) chip, which can be trained to implement certain functions. Usually training of neural networks is done off-line using software tools in the computer system. The neural networks trained off-line are fixed and lack the flexibility of getting trained during usage. In order to(More)
This paper a survey of artificial neural network on various welding technology and also discusses the result based on analysis. The role of optimization techniques in concerned domain with experimental analysis is explained. Refer ences-Parikshik dutta, Dilip Kumar pratihar do modelling of TIF welding process using conventional regression analysis and(More)