This paper describes parallel algorithms for training artifcial neural networks. Possible levels of parallelity are presented. Experiments for checking the effciency of algorithms are discussed.
This paper describes a parallel algorithm for selecting activation functionsrnof an artifcial network. For checking the efficiency of this algorithm a count of multiplicative and additive operations is used.
