Lippermann, R.P., "An Introduction to Computing with Neural Nets," IEEE ASSP Magazine, April 1987, pp. 4-22.  Home/Search   Document Not in Database   Summary   Related Articles

....applied, then the attribute maybe join is equivalent to the maybe join. 2.2 Artificial Neural Networks An artificial neural network is an attempt to mimic the way the human brain works. It offers a new way of solving problems that cannot be efficiently handled by conventional digital computers [13]. Rather than closely depending on the programs that are made for solving clearly defined problems and giving accurate answers, an artificial neural network deals, most of the time, with problems that involve incomplete data set and do not generate straight forward black and white, yes or no ....

....the interconnections among the PEs. In contrast to conventional computers, neural networks are not programmed; rather they are taught. The network adjusts the weights by using certain learning algorithms. The literature has addressed three common classes of learning algorithms for neural networks [13]: supervised, unsupervised, and reinforcement learning. Due to the nature of our underlying environment, the proposed decision support system is based on supervised learning. In the supervised learning, it is necessary to require that each pair of data consist of an input pattern and a ....

Lippermann, R.P., "An Introduction to Computing with Neural Nets," IEEE ASSP Magazine, April 1987, pp. 4-22.

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC