STUPIDSID
1 (a)
What do you mean by learning and list different learning rule.
5 M
1 (b)
Explain Hebbian learning rule.
5 M
1 (c)
Explain Fuzzification and defuzzitication process.
5 M
1 (d)
What are the salient features of Kohonen's self organizing learning algorithm.
5 M
2 (a)
What are the learning strategies in RBF
10 M
2 (b)
Explain perceptron learning rule convergence theorem
10 M
3 (a)
Explain different fuzzy membership function.
10 M
3 (b)
What are the learning factors of back propagation algorithm.
10 M
4 (a)
What is the Hopfield model of neural network ? Explain its algorithm and differentiate discrete and continuous Hopfield model in terms of energy
landscape and stable state.
10 M
4 (b)
i) Compare RBF and MLP
(ii) How do you achieve fast learning in ART 2 network.
(ii) How do you achieve fast learning in ART 2 network.
10 M
5 (a)
Perform two training steps of the network using delta learning rule of λ=1 and c=0.25. Train the network using following data pairs.
\[\left ( x_{1}=\begin{bmatrix} 2\\0 \\-1 \end{bmatrix}d_{1}=-1
Use f(net)=1/0(1-02) \right ), \left ( x_{2} -\begin{bmatrix} 1\\-2 \\-1 \end{bmatrix},d_{2}-1\right )\] The initial weight are w1=[101]t
\[\left ( x_{1}=\begin{bmatrix} 2\\0 \\-1 \end{bmatrix}d_{1}=-1
Use f(net)=1/0(1-02) \right ), \left ( x_{2} -\begin{bmatrix} 1\\-2 \\-1 \end{bmatrix},d_{2}-1\right )\] The initial weight are w1=[101]t
10 M
5 (b)
Find max-min composition and max-product composition.
\[R=\begin{bmatrix} 0.8 &0.1 &0.1 &0.7 \\0 &0.8 &0 &0 \\0.9 &1 &0.7 &0.8 \end{bmatrix} S=\begin{bmatrix} 0.4 &0.9 &0.3 \\0 &0.4 &0 \\0.9 &0.5 &0.8 \\0.6 &0.7 &0.5 \end{bmatrix}\]
\[R=\begin{bmatrix} 0.8 &0.1 &0.1 &0.7 \\0 &0.8 &0 &0 \\0.9 &1 &0.7 &0.8 \end{bmatrix} S=\begin{bmatrix} 0.4 &0.9 &0.3 \\0 &0.4 &0 \\0.9 &0.5 &0.8 \\0.6 &0.7 &0.5 \end{bmatrix}\]
10 M
6 (a)
Explain Back prorogation algorithm.
10 M
6 (b)
If a fuzzy set defined by:
\[A=\frac{0.5}{x_{1}}+\frac{0.4}{x_{2}}+\frac{0.7}{x_{3}}+\frac{1}{x_{4}} \]List all α cuts of set A
\[A=\frac{0.5}{x_{1}}+\frac{0.4}{x_{2}}+\frac{0.7}{x_{3}}+\frac{1}{x_{4}} \]List all α cuts of set A
10 M
Write short note on (any four)
7 (a)
Boltzman machine
5 M
7 (b)
LMS algorithm
5 M
7 (c)
Brain state in box model
5 M
7 (d)
Crossover and mutation
5 M
7 (e)
Bias and threshold in context of artificial neural network
5 M
7 (f)
Method steepest descent
5 M
7 (g)
Fuzzy controller
5 M
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