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检索条件"主题词=Training algorithm"
208 条 记 录,以下是21-30 订阅
排序:
Modulation spectrum-constrained trajectory training algorithm for GMM-based Voice Conversion
Modulation spectrum-constrained trajectory training algorith...
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IEEE International Conference on Acoustics, Speech and Signal Processing
作者: S. Takamichi T. Toda A. W. Black S. Nakamura Grad. Sch. of Inf. Sci. Nara Inst. of Sci. & Technol. (NAIST) Nara Japan
This paper presents a novel training algorithm for Gaussian Mixture Model (GMM)-based Voice Conversion (VC). One of the advantages of GMM-based VC is computationally efficient conversion processing enabling to achieve... 详细信息
来源: 评论
Overcoming Hardware Imperfections in Optical Neural Networks Through a Machine Learning-Driven Self-Correction Mechanism
IEEE PHOTONICS JOURNAL
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IEEE PHOTONICS JOURNAL 2024年 第2期16卷 1页
作者: Kim, Minjoo Kim, Beomju Kim, Yelim Handriani, Lia Saptini Jang, Suhee Jeong, Dae Yeop Yang, Sung Ik Park, Won Il Hanyang Univ Div Mat Sci & Engn Seoul 04763 South Korea Kyung Hee Univ Dept Appl Chem Yongin 17104 South Korea
We developed an optical neural network (ONN) for efficient processing and recognition of 2-dimensional (2D) images, employing a conventional liquid crystal display panel as optical neurons and synapses. This configura... 详细信息
来源: 评论
Recent advancement of remaining useful life prediction of lithium-ion battery in electric vehicle applications: A review of modelling mechanisms, network configurations, factors, and outstanding issues
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ENERGY REPORTS 2024年 11卷 4824-4848页
作者: Reza, M. S. Mannan, M. Mansor, M. Ker, Pin Jern Mahlia, T. M. Indra Hannan, M. A. Univ Tenaga Nas Dept Elect & Elect Engn Kajang 43000 Malaysia Univ Technol Sydney Sch Civil & Environm Engn Ultimo NSW 2007 Australia Sunway Univ Sch Engn & Technol Bandar Sunway 47500 Malaysia Korea Univ Sch Elect Engn Seoul 136701 South Korea
The remaining useful life (RUL) prediction of lithium -ion batteries (LIBs) plays a crucial role in battery management, safety assurance, and the anticipation of maintenance needs for reliable electric vehicle (EV) op... 详细信息
来源: 评论
BASS: Broad Network Based on Localized Stochastic Sensitivity
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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2024年 第2期35卷 1681-1695页
作者: Wang, Ting Zhang, Mingyang Zhang, Jianjun Ng, Wing W. Y. Chen, C. L. Philip South China Univ Technol Sch Med Guangzhou Peoples Hosp 1 Dept Radiol Guangzhou 510006 Peoples R China South China Univ Technol Sch Comp Sci & Engn Guangdong Prov Key Lab Computat Intelligence & Cy Guangzhou 510006 Peoples R China Pazhou Lab Brain & Affect Cognit Res Ctr Guangzhou 510335 Peoples R China South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Peoples R China Dalian Maritime Univ Nav Coll Dalian 116026 Peoples R China
The training of the standard broad learning system (BLS) concerns the optimization of its output weights via the minimization of both training mean square error (MSE) and a penalty term. However, it degrades the gener... 详细信息
来源: 评论
Neural networks trained by weight permutation are universal approximators
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NEURAL NETWORKS 2025年 187卷 107277页
作者: Cai, Yongqiang Chen, Gaohang Qiao, Zhonghua Beijing Normal Univ Sch Math Sci Lab Math & Complex Syst MOE Beijing 100875 Peoples R China Hong Kong Polytech Univ Dept Appl Math Hung Hom Kowloon Hong Kong Peoples R China Hong Kong Polytech Univ Inst Smart Energy Dept Appl Math & Res Hung HomKowloon Hong Kong Peoples R China
The universal approximation property is fundamental to the success of neural networks, and has traditionally been achieved by training networks without any constraints on their parameters. However, recent experimental... 详细信息
来源: 评论
Radar Signal Recognition Based on CSRDNN Network
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IEEE ACCESS 2024年 12卷 86704-86715页
作者: Zhang, Zheng Wan, Chuan Chen, Yi Zhou, Fang Zhu, Xiaofei Zhai, Wenchao Quan, Daying China Jiliang Univ Sch Informat Engn Hangzhou 310018 Peoples R China Xian Res Inst High Technol Xian 710025 Peoples R China
It is essential to achieve the high-accuracy recognition of low probability of intercept (LPI) radar signals in modern electronic warfare. However, under low signal-to-noise ratio (SNR), the recognition accuracy of th... 详细信息
来源: 评论
A novel neural network training framework with data assimilation
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JOURNAL OF SUPERCOMPUTING 2022年 第17期78卷 19020-19045页
作者: Chen, Chong Dou, Yixuan Chen, Jie Xue, Yaru China Univ Petr Coll Informat Sci & Engn Beijing 102249 Peoples R China
In recent years, the prosperity of deep learning has revolutionized the Artificial Neural Networks. However, the dependence of gradients and the offline training mechanism in the learning algorithms prevents the Artif... 详细信息
来源: 评论
Metaheuristic multi-objective optimization with artificial neural networks surrogate modeling for optimal energy-economic performance for CSP technology
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ENERGY AND AI 2025年 20卷
作者: Allouhi, A. Amine, M. Benzakour Aoul, K. A. Tabet USMBA Ecole Super Technol Fes Route ImouzzerBP 2427 Fes Morocco Univ Chouaib Doukkali Fac Sci El Jadida El Jadida 24000 Morocco United Arab Emirates Univ Coll Engn Architectural Engn Dept POB 15551 Al Ain U Arab Emirates
Among CSP technologies, the linear Fresnel reflector (LFR) can provide reliable carbon-neutral electricity for large-scale applications. In this study, the performance of a large solar LFR power plant under varying cl... 详细信息
来源: 评论
A Multi-Objective Decision-Making Neural Network: Effective Structure and Learning Method
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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2025年 第4-5期37卷
作者: Yan, Shu-Rong Nadershahi, Mohadeseh Guo, Wei Ghaderpour, Ebrahim Mohammadzadeh, Ardashir Guangzhou Huashang Coll Sch Digital Finance Guangzhou Peoples R China Payame Noor Univ Dept Ind Engn Tehran Iran Guangdong Univ Finance Sch Credit Management Guangzhou Peoples R China Sapienza Univ Rome Dept Earth Sci Rome Italy Sakarya Univ Dept Elect & Elect Engn Sakarya Turkiye
Decision Neural Networks significantly improve the performance of complex models and create more transparent and accountable decision-making systems that can be trusted in critical applications. However, their perform... 详细信息
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Predicting total biogas potential of food waste using the initial output of biogas potential tests as input data to train an artificial neural network
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BIORESOURCE TECHNOLOGY REPORTS 2024年 26卷
作者: Hunter, Sarah M. Blanco, Edgar Borrion, Adiuan UCL Dept Civil Environm & Geomat Engn Chadwick BldgGower St London WC1E 6BT England Anaero Technol Ltd Cowley Rd Cambridge CB4 0DL England
Quantification of biogas potential is important for predicting anaerobic digestion operability and price. This study uses data from 446 biogas potential tests to train and test a multilayer perceptron artificial neura... 详细信息
来源: 评论