Assignment #5  ECE449, Intelligent Systems in Engineering 


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Assignment #5
ECE449, Intelligent Systems in Engineering
Points: 10

in the assignment box in the ETLC atrium
Note: Show your work! Marks are allocated
for technique and not just the answer.
1. [2 points] Consider a single-input neuron
The input to the neuron is 3.0, its weight is 2.3 and bias is -3.0.
a) What is the net input to the transfer function, tot ?
b) Using an activation function of your choice, determine output of the neuron.
2. [3 points] Consider two single-neuron perceptrons with the same weight and bias values
The first perceptron uses the unipolar hardlimit function, 𝑓hlu, and the second perceptron uses the bipolar
hardlimit function, 𝑓hlb. If the networks are given the same input x, and updated with the perceptron
learning rule, will their weights continue to have the same value?
3. [5 points] Consider two types of activation functions
Logistic sigmoid
tot +e
y= −
(covered in class), and Elliott
y =
(new in this assignment).
a) Determine derivatives of these functions,
b) Plot graphs of the functions and their derivatives,
c) Compare the functions and describe your observations.
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