In this paper, the design of one-pass training algorithms for variant morphological operations is presented. The algorithms intend to achieve a fast-learning goal in which the morphological neurons can learn a training pattern and memorize it in exactly one training iteration. Furthermore, only simple computations are used to allow easy implementation in hardware. The proofs of the training algorithms and the program-simulated experimental results are provided.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Theoretical Computer Science
- Computer Science Applications
- Information Systems and Management
- Artificial Intelligence