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A second kind of neural change often seen with practice is a sharpening of neuronal "tuning functions".
That shrinkage in representation takes place presumably because the narrowing of tuning functions effectively increases the distance between neurons along the dimension that has been trained, thus reducing the total number of neurons that respond to a given stimulus.
The result of that kind of change is that neighbouring neurons will have tuning functions that have less overlap in their responses to stimuli after learning has taken place.
With the help of backstepping design method, the stabilizing functions and tuning functions are constructed.
Moreover, tuning functions are designed to reduce the order of the parameter updater.
Then, an adaptive controller is designed using the tuning functions backstepping technique.
An expansion of the backstepping method is presented based on dynamic gains and tuning functions.
The overparametrization and partial overparametrization problems were soon eliminated by elegantly introducing the tuning functions [33, 35].
We analyze the properties of population codes in terms of the tuning functions that describe individual neuron behavior.
In this paper, an approach for adaptive synchronization of uncertain chaotic systems is proposed using adaptive backstepping with tuning functions.
The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions.
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