Many linear algebra operations, matrix inversions, etc. are required in pattern recognition as well as in signal processing. In this paper, we concentrate on feature extraction pattern recognition techniques (specifically a chord distribution and a moment feature space). For these two case studies, we note the various linear algebra operations required in distortion-invariant pattern recognition. Systolic processors can easily perform all reauired linear algebra functions.
David Casasent, David Casasent,
"Linear Algebra Techniques For Pattern Recognition: Feature Extraction Case Studies", Proc. SPIE 0431, Real-Time Signal Processing VI, (28 November 1983); doi: 10.1117/12.936466; https://doi.org/10.1117/12.936466