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Total No. of Pages : 01
Total No. of Questions : 08
M.Tech.(ECE) (2016 Batch) (Sem.-1)
NEURAL NETWORKS & FUZZY LOGIC
Subject Code : MTEC-104
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M.Code: 74149
Time: 3 Hrs.
Max. Marks : 100
INSTRUCTION TO CANDIDATES :
- Attempt any FIVE questions out of EIGHT questions.
- Each question carry TWENTY marks.
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- Explain Recurrent back propagation method along with its limitations.
- Differentiate clearly between PID, Fuzzy and Fuzzy Neural Control.
- Explain CMAC Networks & ART networks in detail.
- Write short notes on :
- Various Optimization Techniques.
- VLSI implementation of Neural Network
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- What is Fuzzy database? What type of information can be kept in a fuzzy database?
- Distinguish between :
- Feedforward and feedback Neural Network.
- Supervised and Unsupervised Learning.
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- Explain speech recognition system using neural networks.
- Find final weights of a single layer network after three steps of Hebbian learning with bipolar binary neuron used having initial weight vector w = [3 -1 0.5] needs to be trained using the set of three input vectors as below for an arbitrary choice of learning constant =1.
The transposed inputs are :
X1= [2 -2 1.5], X2 = [1 –0.5 -2], X3 = [0 2 -2]
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NOTE : Disclosure of Identity by writing Mobile No. or Making of passing request on any page of Answer Sheet will lead to UMC against the Student.
1| M-74149
(S9)-2201
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