PSYC 421 CH 5 EXAM QUESTIONS WITH VERIFIED SOLUTIONS LATEST UPDATE 2026
The aim of neural network modeling is -- - Answers To approximate the behavior of populations of
neurons
A biological neuron has - Answers A single axon and many dendrites
A sending neuron's axon comes close to a receiving neuron's dendrite at - Answers synapse
All activation functions in artificial neural networks are linear - Answers False
Artificial neural network units with the same inputs but different activation functions can have
different outputs - Answers True
Which of the following mathematical operations is not a function? - Answers Taking square roots
Boolean functions are defined over -- - Answers Truth values
"Neurons that wire together, fire together" is a description of which type of learning? - Answers
Hebbian learning
Perceptron convergence learning does not require feedback about error - Answers False
Any Boolean function can be represented by a single-layer network? - Answers False
The Boolean function OR (inclusive OR) assigns which truth value to the input pair (TRUE, TRUE)? -
Answers True
The Boolean function XOR (exclusive OR) assigns which truth value to the input pair (TRUE, TRUE)? -
Answers False
The Boolean function XOR cannot be represented by a single-layer network because it is not linearly
separable. - Answers True
The perceptron convergence learning rule can be used for both single-layer and multi-layer networks.
It is also present in FB face recognition software. - Answers False
Which of the following is true of feedforward networks? - Answers Activation spreads through the
network in a series of discrete time steps corresponding to the number of layers.
Which type of learning rule can work for networks with hidden units? - Answers backpropagation of
error
Which of the following types of learning is supervised? - Answers the backpropagation algorithm
All learning algorithms for multilayers networks require supervision and feedback. - Answers False
How does an artificial neural network store information? - Answers In the pattern of weights holding
across individual units
There is no clear distinction between information storage and information processing in artificial
neural network models - Answers True
The aim of neural network modeling is -- - Answers To approximate the behavior of populations of
neurons
A biological neuron has - Answers A single axon and many dendrites
A sending neuron's axon comes close to a receiving neuron's dendrite at - Answers synapse
All activation functions in artificial neural networks are linear - Answers False
Artificial neural network units with the same inputs but different activation functions can have
different outputs - Answers True
Which of the following mathematical operations is not a function? - Answers Taking square roots
Boolean functions are defined over -- - Answers Truth values
"Neurons that wire together, fire together" is a description of which type of learning? - Answers
Hebbian learning
Perceptron convergence learning does not require feedback about error - Answers False
Any Boolean function can be represented by a single-layer network? - Answers False
The Boolean function OR (inclusive OR) assigns which truth value to the input pair (TRUE, TRUE)? -
Answers True
The Boolean function XOR (exclusive OR) assigns which truth value to the input pair (TRUE, TRUE)? -
Answers False
The Boolean function XOR cannot be represented by a single-layer network because it is not linearly
separable. - Answers True
The perceptron convergence learning rule can be used for both single-layer and multi-layer networks.
It is also present in FB face recognition software. - Answers False
Which of the following is true of feedforward networks? - Answers Activation spreads through the
network in a series of discrete time steps corresponding to the number of layers.
Which type of learning rule can work for networks with hidden units? - Answers backpropagation of
error
Which of the following types of learning is supervised? - Answers the backpropagation algorithm
All learning algorithms for multilayers networks require supervision and feedback. - Answers False
How does an artificial neural network store information? - Answers In the pattern of weights holding
across individual units
There is no clear distinction between information storage and information processing in artificial
neural network models - Answers True
