Zobrazeno 1 - 10
of 1 312
pro vyhledávání: '"Conditional Mutual information"'
Publikováno v:
Applied Computing and Informatics, Vol 20, Iss 1/2, Pp 55-68 (2024)
Feature selection is an essential step in data mining. The core of it is to analyze and quantize the relevancy and redundancy between the features and the classes. In CFR feature selection method, they rarely consider which feature to choose if two o
Externí odkaz:
https://doaj.org/article/1b42ddce0e52413abde9ba83e8594c43
Publikováno v:
NeuroImage, Vol 292, Iss , Pp 120610- (2024)
Applications of causal techniques to neural time series have increased extensively over last decades, including a wide and diverse family of methods focusing on electroencephalogram (EEG) analysis. Besides connectivity inferred in defined frequency b
Externí odkaz:
https://doaj.org/article/e5b0ffea03464b49bb7050649f99dbc6
Autor:
Dong Wen, Bingbing Liang, Jingjing Li, Lingyu Wu, Xianglong Wan, Xianling Dong, Xifa Lan, Haiqing Song, Yanhong Zhou
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 2370-2380 (2023)
In order to improve the traditional common space pattern (CSP) algorithm pattern in EEG feature extraction, this study proposes a feature extraction method of EEG signals based on permutation conditional mutual information common space pattern (PCMIC
Externí odkaz:
https://doaj.org/article/330262fcb7884bd7a0fad01831474b30
Publikováno v:
Applied Network Science, Vol 7, Iss 1, Pp 1-22 (2022)
Abstract In this work, we introduce a new methodology for inferring the interaction structure of discrete valued time series which are Poisson distributed. While most related methods are premised on continuous state stochastic processes, in fact, dis
Externí odkaz:
https://doaj.org/article/ad553e2829bd4528a09a999b49134299
Akademický článek
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Akademický článek
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Autor:
Haibo LAN
Publikováno v:
大数据, Vol 8, Pp 133-144 (2022)
Attribute reduction is an important research content of the rough set theory.Its main purpose is to eliminate irrelevant attributes in information systems, reduce data dimensions and improve data knowledge discovery performance.However, most of the a
Externí odkaz:
https://doaj.org/article/6b0959c87d1a48fa89d8f3f9dae1932e
Publikováno v:
Frontiers in Genetics, Vol 14 (2023)
Gene co-expression networks are a useful tool in the study of interactions that have allowed the visualization and quantification of diverse phenomena, including the loss of co-expression over long distances in cancerous samples. This characteristic,
Externí odkaz:
https://doaj.org/article/c59eb01fd300422d938fe6cbc82840e3
Publikováno v:
IET Electric Power Applications, Vol 16, Iss 5, Pp 548-564 (2022)
Abstract Precise forecasting of the thermal parameters is a critical factor for the safe operation and fault incipient warning of the ultra‐high voltage (UHV) transformers. In this work, a novel multi‐step forecasting method based on the long‐
Externí odkaz:
https://doaj.org/article/c71a57c48efe4f93b75bca5ee110b7aa
Publikováno v:
IEEE Access, Vol 10, Pp 87254-87265 (2022)
In this paper, we propose a novel curiosity-based learning algorithm for Multi-agent Reinforcement Learning (MARL) to attain efficient and effective decision-making. We employ the centralized training with decentralized execution framework (CTDE) and
Externí odkaz:
https://doaj.org/article/ea341c98ba52493b8fe43c46f77bd8a6