Howard B. Demuth

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  • Design—Martin T. Hagan, Howard B. Demuth
  • IEEE Transactions on Neural Networks
  • 1997
This book gives an introduction to basic neural-network architectures 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)
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)
Parikshik dutta, Dilip Kumar pratihar do modelling of TIF welding process using conventional regression analysis and neural network-based approaches. journal of Materials Processing Technology 184 (2007) 56–68 P. Sathiya ?, K. Panneerselvam, M. Y. Abdul Jaleel "Optimization of laser welding process parameters for super austenitic stainless steel using(More)
Stock market prediction plays a vital rule in taking financial decisions. Various factors affecting the stock market makes stock prediction somewhat complex and difficult. Different data mining techniques such as Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS) etc are being widely used for predicting stock prices of different(More)
In this paper we describe four parallel merge-sort algorithms: (I) Parallel merging; (2) Bubble/merge; (3) Batcher's odd-even merge; and (4) Quicksort/merge. In each algorithm we divide a sequence of numbers of length n into k subsequences of equal length. Using k processors we sort each subsequence using a serial algorithm, either Merge-sort, Bubble,(More)
Today, investment by purchasing stock-share constitutes the greater part of economic exchange of countries and a considerable amount of capital is exchanged through the stock markets in the whole world. But one of the most important problems is finding efficient ways to summarize and visualize the stock market data to individual or institutions useful(More)
The main intension of this work is to present the importance of neural chip with learning capability. The designed sequentially trained MLP structure is used to solve the classical XOR problem and the structure is realized on FPGA device environment. By comparing the device utilization summary for the design in different families of Xilinx FPGA, the(More)