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FIGURE 12.14 is a schematic of the target-tracking predictor-corrector model. This causal model takes the form of a dynamic Bayesian network. Random variables T and V stand for target position and visual input, respectively, and (t) represents discrete time in steps from 1 to n. The position of the target on any time step can be probabilistically inferred from the position of the target on the previous time step and the visual input on the current time step.This tool is built from the MATLAB scripts for Tutorial on Neural Systems Modeling by Thomas J. Anastasio.
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