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Chapter 8.2 pt 2

CGSC170 Chapter 8.2 pt 2:


Department
Cognitive Science
Course Code
CGSC170
Professor
Kaja Jasinka
Chapter
8.2 pt 2

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Connection to Neural NEtworks
Network units in the domain and range connection can represent binary Boolean
functions.
First they must represent Boolean functions using numbers
Need numbers for input/output values
Ex- True= 1 and False= 0
If this only produces 1 or 0 as inputs and outputs than it is a
Boolean Function
If there are 2 inputs than it is binary Boolean
3 inputs= ternary Boolean
Designing Networks to take 0 and 1 as outputs
Binary threshold activation functions
These functions output 0 until the threshold is reached
Then it outputs 1
THe weights and the threshold must be set in a way that replicates the
truth table for a Boolean Function to represent this function
There are “x”-nary Boolean function for every natural number “x”
The only one scientists focus on is the Unary function
NOT
NOT A is true if A is false
NOT A is false if A is true
Individual neuron-like units can achieve a lot
A single unit can represent basic Boolean Functions
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