problem 1)a) Along with the block diagram and equations, describe the model of a neuron.

b) What is memory based learning? What are the two necessary ingredients of memory based learning?

c) Consider a 3-class problem and K-nearest neighbor classifier with K=5. Given a Xtest, K-nearest neighbor produces the {x1,x2,x3,x4,x5} neighbors from the training set. If {x1} class-1, {x2,x3,x4} class-2 and {x5} class-3. Then what is the class predicted by Knearest neighbor? Justify.

problem 2)a) Using necessary equations prove the perceptron convergence theorem.

problem 3)a) Along with neat diagram describe the state-space model.

b) prepare down the differences between recurrent autoassociative network and recurrent heteroassociative network.

problem 4)a) Describe two basic models for feature map. Also describe two phases of adaptive process used in SOM.

b) In the self organizing maps, how cooperative process is different from competitive process? Also provide different equations involved in cooperative and competitive processes.

c) prepare idempotency and commutativity properties of fuzzy sets.

problem 5)a) What is fuzzy inference engine? In fuzzy inference engine for computing heart attack risk, one of the inputs is electrocardiogram. Describe three different ways of inputing electrocardiogram to this inference engine.

problem 6)a) Describe the fuzzy classification networks using backpropagation and fuzzy associative memories.