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2003 Course Artificial Neural Networks

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Total No. of Questions : 12] [Total No. of Pages : 4 [3764]-228 P1347 B.E. (E & T C) ARTIFICIAL NEURAL NETWORKS (404218) (2003 Course) Time : 3 Hours] [Max. Marks : 100 Instructions to the candidates : 1) Answer Q.1 or Q.2, Q.3 or Q.4, Q.5 or Q.6 from Section I. Q.7 or Q.8, Q.9 or Q.10, Q11 or Q12 from Section II. 2) Answers to the two sections should be written in separate answer books. 3) Neat diagrams must be drawn wherever necessary. 4) Use of electronic pocket calculator is allowed. 5) Assume suitable data, if necessary. SECTION - I Q1) a) Compare the performance of a computer and that of a biological neural network in terms of speed of processing, size and complexity, storage, fault tolerance and control mechanism. [6] b) Compare LMS, perceptron and delta learning laws. c) A 2 input neurons with the following parameter is given : = 1 .2, W = [3, 2] and I = [ 5, 6]. Calculate the neuron output for the following transfer function. [6] i) Symmetrical hard limit function. ii) [6] Saturating linear function. OR Q2) a) What are the main differences among the three modes of artificial neuron, namely, McCulloch-Pitts, perceptron and Adaline? [6] b) What is reinforcement learning? In what way is it different from supervised learning? [6] c) What is meant by operating range of neuron? [3] d) Explain what is Hebbian learning. [3] Draw the architecture of multilayer feedforward network. [4] Q3) a) P.T.O.

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