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THE MODAL FEATURES OF THE VIBRATION SYSTEMS OF THE WEAKLY- VISCOELASTIC MATERIAL STRUCTURES
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作者 Chen Guo-ping and Zhu De-maoNanjing Aeronautical Institute 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 1991年第4期347-353,共7页
This paper discusses the modal features of weakly-viscoelastic material structures both for single-modulus and multi-modulus materials. It is the eigenvalues of these structures that are the roots of a series of ratio... This paper discusses the modal features of weakly-viscoelastic material structures both for single-modulus and multi-modulus materials. It is the eigenvalues of these structures that are the roots of a series of rational fraction polynomial equations. A theorem about the roots of these equations is proved in the paper. Based on it, some important conclusions about the modal features of the weakly viscoelastic material structures are given according to their dynamic behaviors. 展开更多
关键词 VISCOELASTIC MATERIAL STRUCTURES THE MODAL featureS OF THE VIBRATION SYSTEMS OF THE WEAKLY REAL
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Modal Interactive Feature Encoder for Multimodal Sentiment Analysis
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作者 Xiaowei Zhao Jie Zhou Xiujuan Xu 《国际计算机前沿大会会议论文集》 EI 2023年第2期285-303,共19页
Multimodal Sentiment analysis refers to analyzing emotions in infor-mation carriers containing multiple modalities.To better analyze the features within and between modalities and solve the problem of incomplete multi... Multimodal Sentiment analysis refers to analyzing emotions in infor-mation carriers containing multiple modalities.To better analyze the features within and between modalities and solve the problem of incomplete multimodal feature fusion,this paper proposes a multimodal sentiment analysis model MIF(Modal Interactive Feature Encoder For Multimodal Sentiment Analysis).First,the global features of three modalities are obtained through unimodal feature extraction networks.Second,the inter-modal interactive feature encoder and the intra-modal interactive feature encoder extract similarity features between modal-ities and intra-modal special features separately.Finally,unimodal special features and the interaction information between modalities are decoded to get the fusion features and predict sentimental polarity results.We conduct extensive experi-ments on three public multimodal datasets,including one in Chinese and two in English.The results show that the performance of our approach is significantly improved compared with benchmark models. 展开更多
关键词 Multimodal Sentiment Analysis Modal Interaction feature ENCODER
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