基于镜像神经网络的模式识别和记忆映射
Pattern Recognition and Memory Mapping using Mirroring Neural Networks
摘要：
在本文中，我们提出了一种新的学习实现模式识别使用镜像神经网络（MNN）的概念，它可以从不同的感官输入模式中提取信息，并执行模式识别任务。它还能够被用作高级关联存储器，其中图像数据以无监督的方式与语音输入相关联。由于体系结构是分层和模块化的，它有可能被用来设计不断增加的复杂性的学习引擎。
英文摘要：
In this paper, we present a new kind of learning implementation to recognize the patterns using the concept of Mirroring Neural Network (MNN) which can extract information from distinct sensory input patterns and perform pattern recognition tasks. It is also capable of being used as an advanced associative memory wherein image data is associated with voice inputs in an unsupervised manner. Since the architecture is hierarchical and modular it has the potential of being used to devise learning engines of ever increasing complexity.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
