基于远程的延迟网络中的内存非线性权衡

Stefan Iacob1, Joni Dambre1

  • 1IDLab-AIRO, Faculty of Engineering and Architecture, Ghent University, 9052 Ghent, Belgium.

PubMed
概括

基于距离的延迟网络 (DDN) 与回声状态网络 (ESN) 相比,为时间模式学习提供了更好的内存容量和非线性处理. 这项研究表明,DDN在内存和非线性之间实现了卓越的平衡,提高了复杂任务的性能.

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