3. In an automatic character recognition system according to claim 1, a scanning and training structure further including a plurality of k of said storage plane means, wherein said digital scanning means repeatedly scans said first known character indicia k times, each of said k scans being performed using a different set of selected scan parameters for producing k binary encoded path vectors in the form of k separate milti-bit binary words, wherein said complex inner product function performing means performs the complex inner product function of each of said k binary encoded path vectors and each of said stored canonic shapes to produce k separate pluralities of complex numbers encoded in binary form, each one of said k separate pluralities of encoded complex numbers including an encoded complex number for each complex inner product performed with each canonic shape and a separate different one of said k binary encoded path vectors, each of said binary encoded complex inner product numbers including a magnitude value representative of the similarity between its associated one of said k binary encoded path vectors and each of said canonic shapes, and an angle value representative of the angular offset of its associated one of said k binary encoded path vectors relative to each of said canonic shapes, wherein said magnitude determining and recording means and said shape index and angle value encoding means provide a plurality of k separate of N bit vectors, one for each of said k different scans, said k separate N bit vectors being representative of the shape index and angle value of the largest magnitude inner complex number produced by each of said k scan path vectors and said plurality of canonic shapes, and wherein said storage indicia entering means enters a separate storage indicia into each of said k storage planes at discrete storage locations corresponding to the column associated with said first known character and to the row associated with each of said separate encoded N bit vectors associated with said recorded shape index and angle value produced relative to each of said separate k scans using a different set of selected scan parameters.
3. In an automatic character recognition system according to claim 1, a scanning and training structure further including a plurality of k of said storage plane means, wherein said digital scanning means repeatedly scans said first known character indicia k times, each of said k scans being performed using a different set of selected scan parameters for producing k binary encoded path vectors in the form of k separate milti-bit binary words, wherein said complex inner product function performing means performs the complex inner product function of each of said k binary encoded path vectors and each of said stored canonic shapes to produce k separate pluralities of complex numbers encoded in binary form, each one of said k separate pluralities of encoded complex numbers including an encoded complex number for each complex inner product performed with each canonic shape and a separate different one of said k binary encoded path vectors, each of said binary encoded complex inner product numbers including a magnitude value representative of the similarity between its associated one of said k binary encoded path vectors and each of said canonic shapes, and an angle value representative of the angular offset of its associated one of said k binary encoded path vectors relative to each of said canonic shapes, wherein said magnitude determining and recording means and said shape index and angle value encoding means provide a plurality of k separate of N bit vectors, one for each of said k different scans, said k separate N bit vectors being representative of the shape index and angle value of the largest magnitude inner complex number produced by each of said k scan path vectors and said plurality of canonic shapes, and wherein said storage indicia entering means enters a separate storage indicia into each of said k storage planes at discrete storage locations corresponding to the column associated with said first known character and to the row associated with each of said separate encoded N bit vectors associated with said recorded shape index and angle value produced relative to each of said separate k scans using a different set of selected scan parameters. 4. In an automatic character recognition system according to claim 3, a scanning and training structure wherein said manifesting and processing means processes and manifests a plurality of different known characters from said character class in sequence and wherein said operation functions of said scanning and training structure are repeated for each of said different known characters of said plurality to produce storage indicia in each of said k storage planes at discrete storage locations corresponding to the columns associated with of said plurality of different known characters and to the rows associated with said recorded shape indicies and angle values produced relative to each of said separate k scans using different sets of selected scan parameters for said plurality of different known characters.