The Use of Local Linear Transforms to Reduce the Size of a Two-Dimensional Associative Memory
We discuss associative memory in the analysis of two-dimensional data where the variables are transformed before data accumulation. Local linear transforms reduce the number of associative locations required, while a two-dimensional search scheme shortens the search among the fewer locations. Application of these methods results in some saving of memory space and an appreciable saving in execution time.