feedforward

Classification algorithms can use prototypes or templates {feedforward}. Classification results when stimulus parts closely match prototype or template parts.

feedforward mechanism

Input can regulate output {feedforward mechanism}, by sending signals based on system states and environment to enhance or initiate actions. Feedforward sets output level based on algorithm or system model. After sending feedforward signal, system sends no more signals for a time {refractory period, feedforward}, to allow time to check first-signal results.

examples

Feedforward classification algorithms include feature-based winner-take-all algorithms {Pandemonium algorithm}, feedforward neural nets using feedback during learning {backpropagation, feedforward}, tree-based classifiers, and parametric statistical modeling [Selfridge, 1970].

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Date Modified: 2022.0224