Image recognition with inexact processing

Shannon has shown that one can communicate exactly over a noisy channel. It thus stands to reason that one can compute accurately with an inexact processor. For example, optical processors offer advantages of massive parallelism and great speed but suffer from significant inexactitude. Another example is wafer-scale VLSI processors, which can be inexact due to a distribution of defects. We propose an architecture whereby the accuracy of matched filter processors can be improved significantly at the cost of a modest increase in computational intensity. Errors due to noisy data and/or inexact computing can be detected and in some cases corrected. We show that over one million objects can potentially be detected with single error correction capability using only 25 (composite) matched filters.