We demonstrate a simple connection between dictionary methods for time series classification, which involve extracting and counting symbolic patterns in time series, and methods based on transforming input time series using convolutional kernels, namely ROCKET and its variants. We show that by adjusting a single hyperparameter it is possible to move by degrees between models resembling dictionary methods and models resembling ROCKET. We present HYDRA, a simple, fast, and accurate dictionary method for time series classification using competing convolutional kernels, combining key aspects of both ROCKET and conventional dictionary methods. HYDRA is faster and more accurate than the most accurate existing dictionary methods, and can be combined with ROCKET and its variants to further improve the accuracy of these methods.
HyDRA: A Hybrid Dual-Mode Network for Closed- and Open-Set RFFI with Optimized VMD
School of Electronics and Communication Engineering, Sun Yat-sen University（中山大学电子与通信工程学院）；School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University（上海交通大学电子信息与电气工程学院）；School of Electronic Information and Electrical Engineering, Dalian Maritime University（大连海事大学电子信息与电气工程学院）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）
Accurate Discharge Coefficient Prediction of Streamlined Weirs by Coupling Linear Regression and Deep Convolutional Gated Recurrent Unit
Wenzhou University（温州大学）；Wenzhou Polytechnic（温州职业技术学院）；National Yunlin University of Science and Technology（云林科技大学）；Hong Kong Polytechnic University（香港理工大学）；Obuda University（奥布达大学）；Slovak University of Technology in Bratislava（斯洛伐克布拉迪斯拉发工业大学）
Saarland University（萨尔兰大学）；Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）；Huawei Noah’s Ark Lab（华为诺亚方舟实验室）；Max Planck Institute for Software Systems（马克斯·普朗克软件系统研究所）
Fusion of Quadratic Time-Frequency Analysis and Convolutional Neural Networks to Diagnose Bearing Faults Under Time-Varying Speeds
Faculty of Information Technology and Communication Sciences, Tampere University（信息科技与通信科学学院，塔尔皮莱大学）；Faculty of Medicine and the Department of Clinical Neurophysiology at the University of Helsinki and Helsinki University Hospital（医学学院及赫尔辛基大学临床神经生理学系，赫尔辛基大学医院）；Department of Electrical Engineering, Qatar University（电气工程系，卡塔尔大学）
