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Efficient Sparse Coding in Early Sensory Processing: Lessons from Signal Recovery
Figure 3
The impact of 
on the signal decomposition and the overall quality of the sparse coding filters.
(A) The empirical distribution of the Gabor patch fitting error as a function of 
. Larger spread signifies deviation from ideal Gabor patch, often used as model shape for experimentally recorded receptive fields. The shift of the mean toward 
as 
increases is a consequence of the decrease of the average filter size. For each mean value a sample filter is shown demonstrating this shrinkage effect. (B) The dimension and the relative weight of L (the low dimensional signal) in the reconstruction as a function of 
. Relevant range is where the dimensionality is low, yet L is able to capture most of the original signal. For image size 16×16 this range is about 0.3–0.8.
doi: https://doi.org/10.1371/journal.pcbi.1002372.g003