Neural networks in APL

ABSTRACT

Neural networks are fairly straightforward to program in a matrix oriented language such as APL. The only general improvement that would benefit them would be the implementation of sparse matrics. Small networks can be trained quite easily using the standard procedures (back propagation, etc).

REFERENCES

• 1: Hopfield, J.J. Neural networks and physicat systems with emergent collective computational abilities. Proc. Nat. Acad. Sci. USA, Vol. 79, 2554-2558, 1982.
• 2: Minsky, M., Papert, S. Perceptrons: an introduction to computational geometry. MIT Press, Cambridge, Mass., 1965.

INDEX TERMS

Primary Classification:
  D. Software
  D.3 PROGRAMMING LANGUAGES
      D.3.2 Language Classifications

          Nouns: APL

Additional Classification:
  C. Computer Systems Organization
  C.1 PROCESSOR ARCHITECTURES

  F. Theory of Computation
  F.2 ANALYSIS OF ALGORITHMS AND PROBLEM COMPLEXITY
      F.2.1 Numerical Algorithms and Problems
          Subjects: Computations on matrices
      F.2.2 Nonnumerical Algorithms and Problems
          Subjects: Computations on discrete structures

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE

General Terms:
Algorithms, Languages