{"title":"Attractor Properties of Spatiotemporal Memory in Effective Sequence Processing Task","authors":"P. Kuderov, E. Dzhivelikian, A. I. Panov","doi":"10.3103/S1060992X23060097","DOIUrl":null,"url":null,"abstract":"<p>For autonomous AI systems, it is important to process spatiotemporal information to encode and memorize it and extract and reuse abstractions effectively. What is natural for natural intelligence is still a challenge for AI systems. In this paper, we propose a biologically plausible model of spatiotemporal memory with an attractor module and study its ability to encode sequences and efficiently extract and reuse repetitive patterns. The results of experiments on synthetic and textual data and data from DVS cameras demonstrate a qualitative improvement in the properties of the model when using the attractor module.</p>","PeriodicalId":721,"journal":{"name":"Optical Memory and Neural Networks","volume":"32 2","pages":"S284 - S292"},"PeriodicalIF":1.0000,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.3103/S1060992X23060097.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optical Memory and Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.3103/S1060992X23060097","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OPTICS","Score":null,"Total":0}
引用次数: 0
Abstract
For autonomous AI systems, it is important to process spatiotemporal information to encode and memorize it and extract and reuse abstractions effectively. What is natural for natural intelligence is still a challenge for AI systems. In this paper, we propose a biologically plausible model of spatiotemporal memory with an attractor module and study its ability to encode sequences and efficiently extract and reuse repetitive patterns. The results of experiments on synthetic and textual data and data from DVS cameras demonstrate a qualitative improvement in the properties of the model when using the attractor module.
期刊介绍：
The journal covers a wide range of issues in information optics such as optical memory, mechanisms for optical data recording and processing, photosensitive materials, optical, optoelectronic and holographic nanostructures, and many other related topics. Papers on memory systems using holographic and biological structures and concepts of brain operation are also included. The journal pays particular attention to research in the field of neural net systems that may lead to a new generation of computional technologies by endowing them with intelligence.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
