ADAPTIVE-NETWORK-BASED FUZZY INFERENCE SYSTEMS


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Set Operations

• Containment or Subset,
• Union (disjunction),
• Intersection (conjunction),
• Complement (negation),
• Probabilistic AND,
• Probabilistic OR.

Partition styles for fuzzy models

• Grid partition - often chosen in designing a fuzzy controller,
problems when we have moderately large number of inputs.
• Tree partition - relives the problem of an exponential increase
in the number of rules.
• Scatter partition.

ADAPTIVE NETWORKS

• Back-propagation neural network.
• Radial basis function network.
• Adaptive network
◊ Overall input-output behaviour is determined by the values
of a collection of modifiable parameters.
◊ Each node is a process unit that performs a static node
function on its incoming signals and generate a single node
output.
◊ Each page link specifies the direction of signal flow from one
node to another.
◊ Usually a node function is a parametrized function with
modifiable parameters; by changing this parameters, we are
changing the node function.
◊ In most general case, an adaptive network is heterogeneous
and each node may have a different node function.
◊ A node parameter set can be non-empty - adaptive node or
empty - fixed node.