The results are discussed by comparing the simulations of different logic functions with both types of inputs. It contains the results of an initial study of supervised training the network with binary and bipolar input data. single- and multi-layer perceptron, using VHDL. This paper discusses the implementation of two artificial neural networks, i.e. Fast learning helps in increased usage of artificial neural networks. student, M.B.M Engineering College, Jodhpur, IndiaĪbstract:–The training speed of the artificial neural network is affected by choice of initial value of weights and also on the input data representation. Sanjay Bhandari1Īssociate Professor, Department of Electronics & Communication Engineering, Jodhpur Institute of Engineering & Technology, Jodhpur, IndiaĢ-M.E. Modeling of Adaptive Artificial Neural Networks using VHDL is More Appropriate using Bipolar Inputs
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