Information is stored using convolution and retrieved using correlation.
The result of correlation is a blurry but potentially interpretable vector. The way the model interprets this vector, f' j , is to compute the dot product between the recovered vector and the possible candidates and if this value is within acceptable limits, then the item is interpreted and produced. The number of elements should be an odd number. Alpha is a noise or forgetting parameter and lambda is a weighting factor that increases or decreases the relative importance of item information. There are three retrieval modes, which have to do with the composition of the competitor set.