Pattern Association
- Associative memory- Learns by association
 
- Autoassociation- Store a set of patterns by repeatedly presenting them in the network- Then presented partial or distorted stored pattern
- Recall intended
 
- Input and output data spaces are same dimensionality
 
- Store a set of patterns by repeatedly presenting them in the network
- Heteroassociation- Arbitrary set of input patterns paired with another arbitrary set of output patterns- Supervised instead of unsupervised
 
- No required relationship between input/output dimensionality
 
- Arbitrary set of input patterns paired with another arbitrary set of output patterns
- Stages- Storage
- Recall
 
Pattern Recognition
- Received pattern/signal is assigned to one of a prescribed number of classes
 
Function Approximation
- System Identification
 
- Inverse System
 
Control
- Learn to control a process or critical part of a system
Filtering
- Filtering- Extraction of information about a quantity of interest at discrete time by using data from time up to
 
- Smoothing- Use information past time - Expect smoother result
 
- Delay in processing
 
- Use information past time 
- Prediction- Predict later data using current and previous
 
Beamforming
- Spatial filtering
- Distinguish spatial properties of a target signal and background noise- Similar to bats
- Used in radar and sonar