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Neural Networks Question Paper

Neural Networks

Course:Bachelor Of Science In Information Technology

Institution: Kca University question papers

Exam Year:2010

UNIVERSITY EXAMINATIONS: 2010/2011
FIRST YEAR STAGE EXAMINATION FOR THE DEGREE OF BACHELOR
OF SCIENCE IN INFORMATION TECHNOLOGY
BIT 4404: NEURAL NETWORKS
DATE: DECEMBER 2010 TIME: 2 HOURS
INSTRUCTIONS: Answer question ONE and any other TWO questions
QUESTION ONE
a) briefly explain the following concepts
i. learning (2 Marks)
ii. neural networks (2 Marks)
iii. Artificial Neuron (2 Marks)
b) Describe four motivations of machine learning technology (4 Marks)
c) briefly explain five components of a learning agent (4 Marks)
d) Describe the importance of the following components of a biological neuron (5 Marks)
i. Soma
ii. Dendrite
iii. Axon Hillock
iv. Myelin sheath
v. Nodes of ranvier
e) Briefly explain how information flow in a neural cell (6 Marks)
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f) Describe the significance of synapse strength between any two neurons (2 Marks).
g) Briefly explain three applications that are performed by artificial neural networks. (3 Marks)
QUESTION TWO
a) Briefly describe the flow of information in Mcculloch-pitts Neuron (4 Marks).
b) state any three features that are missing in mcculloch-pitts neuron model (3 Marks)
c) Artificial neuron consists of four basic components. Describe each of these components. Use a
diagram to illustrate your answer (6 Marks)
d) There are two types of threshold functions. State and explain each of them. Use a diagram to
illustrate your answer (6 Marks)
e) Explain the significance of synapse strength in a biological neuron (1 Mark)
QUESTION THREE
a) Briefly explain the meaning of the following terms
i. back propagation (2 Marks)
ii. Network training: (2 Marks)
iii. Epoch (2 Marks)
b) Briefly explain five properties of neural networks (5 Marks)
c) Describe four challenges of implement neural networks in machine learning (4 Marks)
d) Neural network has three main types of layers. State and explain each of these layers.
Use a diagram to illustrate your answer (4 Marks)
e) Explain the meaning of the term ‘activation’ (1 Mark).
QUESTION FOUR
a) Briefly explain the meaning of the following terms
i. Bias (2 Marks).
ii. Convergence (2 Marks)
iii. SOM (2 Marks)
b) Briefly explain any four situations recommended for ANN. (4 Marks).
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c) State any three parameters that are set in neural networks (3 Marks)
d) State and explain three types of training network (3 Marks)
e) State and explain two properties of a self organizing network (4 Marks)
QUESTION FIVE
a) Briefly explain the meaning of the term ‘hope field network’. Use a diagram to illustrate your
answer. (3 Marks).
b) Describe four properties of hope field network (4 Marks)
c) Use back propagation algorithm to compute one training pass on the following neural network.
(6 Marks)
Target = 0.5, Learning rate = 1
d) State and explain any two types radial basis functions (4 Marks)
e) Explain the problem addressed by ‘stability-plasticity dilemma’ in the context of Adaptive
resonance theory (1 Mark).
f) Explain types of Adaptive resonance theory architectures (2 Marks)

Neural Networks Question Paper

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