ADAPTIVE-NETWORK-BASED FUZZY INFERENCE SYSTEMS

[velmurugan]

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.