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Artykuły w czasopismach na temat "Short-time features"
Martinez-Heath, M. R., i A. G. Deacon. "Engineering Risk Assessment in Manufacturing Products with Short Time-to-Market Windows". Journal of Engineering for Industry 117, nr 1 (1.02.1995): 49–54. http://dx.doi.org/10.1115/1.2803277.
Pełny tekst źródłaBehzad, M., A. R. Bastami i D. Mba. "Rolling bearing fault detection by short-time statistical features". Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering 226, nr 3 (19.10.2011): 229–37. http://dx.doi.org/10.1177/0954408911422635.
Pełny tekst źródłaAkulenko, L. D., Yu G. Markov, V. V. Perepelkin i L. V. Rykhlova. "Short-time-scale features of the Earth’s polar motion". Astronomy Reports 53, nr 11 (listopad 2009): 1070–77. http://dx.doi.org/10.1134/s1063772909110122.
Pełny tekst źródłaHeinen, Marco, Peter Holmqvist, Adolfo J. Banchio i Gerhard Nägele. "Short-time diffusion of charge-stabilized colloidal particles: generic features". Journal of Applied Crystallography 43, nr 5 (19.08.2010): 970–80. http://dx.doi.org/10.1107/s002188981002724x.
Pełny tekst źródłaRiest, Jonas, i Gerhard Nägele. "Short-time dynamics in dispersions with competing short-range attraction and long-range repulsion". Soft Matter 11, nr 48 (2015): 9273–80. http://dx.doi.org/10.1039/c5sm02099a.
Pełny tekst źródłaSundararajan, Narasimman, A. Ebrahimi i Nannappa Vasudha. "Two Dimensional Short Time Hartley Transforms". Sultan Qaboos University Journal for Science [SQUJS] 21, nr 1 (1.11.2016): 41. http://dx.doi.org/10.24200/squjs.vol21iss1pp41-47.
Pełny tekst źródłaRamalingam, A., i S. Krishnan. "Gaussian Mixture Modeling of Short-Time Fourier Transform Features for Audio Fingerprinting". IEEE Transactions on Information Forensics and Security 1, nr 4 (grudzień 2006): 457–63. http://dx.doi.org/10.1109/tifs.2006.885036.
Pełny tekst źródłaRusnak, Yu. "SEMANTIC AND STRUCTURAL FEATURES OF TIME ADVERBS IN OLGA KOBYLYANSKA’S SHORT PROSE". International Humanitarian University Herald. Philology 2, nr 46 (2020): 104–7. http://dx.doi.org/10.32841/2409-1154.2020.46-2.25.
Pełny tekst źródłaSun, Dechao, Jiali Wu, Hong Huang, Renfang Wang, Feng Liang i Hong Xinhua. "Prediction of Short-Time Rainfall Based on Deep Learning". Mathematical Problems in Engineering 2021 (30.03.2021): 1–8. http://dx.doi.org/10.1155/2021/6664413.
Pełny tekst źródłaQiao, Mu, i Zixuan Cheng. "A Novel Long- and Short-Term Memory Network with Time Series Data Analysis Capabilities". Mathematical Problems in Engineering 2020 (13.10.2020): 1–9. http://dx.doi.org/10.1155/2020/8885625.
Pełny tekst źródłaRozprawy doktorskie na temat "Short-time features"
Mubarak, Omer Mohsin Electrical Engineering & Telecommunications Faculty of Engineering UNSW. "Speech and music discrimination using short-time features". Awarded by:University of New South Wales. Electrical Engineering & Telecommunications, 2006. http://handle.unsw.edu.au/1959.4/31954.
Pełny tekst źródłaDíaz, González Fernando. "Federated Learning for Time Series Forecasting Using LSTM Networks: Exploiting Similarities Through Clustering". Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254665.
Pełny tekst źródłaFederated Learning utgör en statistisk utmaning vid träning med starkt heterogen sekvensdata. Till exempel så uppvisar tidsseriedata inom telekomdomänen blandade variationer och mönster över längre tidsintervall. Dessa distinkta fördelningar utgör en utmaning när en nod inte bara ska bidra till skapandet av en global modell utan även ämnar applicera denna modell på sin lokala datamängd. Att i detta scenario införa en global modell som ska passa alla kan visa sig vara otillräckligt, även om vi använder oss av de mest framgångsrika modellerna inom maskininlärning för tidsserieprognoser, Long Short-Term Memory (LSTM) nätverk, vilka visat sig kunna fånga komplexa mönster och generalisera väl till nya mönster. I detta arbete visar vi att genom att klustra klienterna med hjälp av dessa mönster och selektivt aggregera deras uppdateringar i olika globala modeller kan vi uppnå förbättringar av den lokal prestandan med minimala kostnader, vilket vi demonstrerar genom experiment med riktigt tidsseriedata och en grundläggande LSTM-modell.
Dai, Shin-Hao, i 戴欣浩. "Feature Selection and Feature Extraction for Emotion Recognition Based on Multiple Short-Time Physiological Signals". Thesis, 2015. http://ndltd.ncl.edu.tw/handle/78424722899130791289.
Pełny tekst źródła國立中正大學
電機工程研究所
103
In this paper, we proposed an emotion recognition system based on three short-time physiological signals. Electrocardiogram (ECG), Photoplethysmorgraphy (PPG) and Skin Impedance (SI) were used to recognize five kinds of negative emotions, including neutral (non-stimulated state), sad, stress, anger and disgust. In our study, we aimed to develop a user-independent system. This emotion recognition system was composed of data acquisition (physiological signals), feature calculation, normalization, feature selection or feature extraction, and classification. First, in the data acquisition part, 50 subjects were recruited to participate in this study, including 22 males and 28 females. By employing visual and audio stimulation, the subject emotions were induced and the signals were recorded. Second, in the feature calculation part, we calculated 7 types ECG features from wave-form and HRV sequence, 10 types PPG features from wave-form and HRV sequence and 3 types SI features from wave-form and SCR sequence. Totally, 140 features were calculated. Third, we normalized our feature set to the same level. Fourth, in the feature selection part, we performed Genetic Algorithm (GA) to select the most effective feature set to enhance accuracy. On the other hand, the feature extraction part, we compared the performance of the Principal Component Analysis (PCA), Independent Component Analysis (ICA), Linear Discriminant Analysis (LDA) and 3 modified LDA (OLDA, SLDA and RLDA) methods in reducing the feature dimensions by mapping the original data to the better subspace. Finally, we used SVM to classify emotions. And we performed leave-one-out scheme for cross validation. According to the result, the accuracy were 70.4% when using GA feature selector, 67.6% when using OLDA feature extractor, 95.2% when using OLDA feature extractor in combination with the GA feature selector.
Książki na temat "Short-time features"
Allen, Robert C. The Industrial Revolution: A Very Short Introduction. Oxford University Press, 2017. http://dx.doi.org/10.1093/actrade/9780198706786.001.0001.
Pełny tekst źródłaCharon, Rita. A Framework for Teaching Close Reading. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199360192.003.0009.
Pełny tekst źródłaStokes, Lisa Odham. Food for Thought: Cannibalism in The Untold Story and Dumplings. Edinburgh University Press, 2018. http://dx.doi.org/10.3366/edinburgh/9781474424592.003.0011.
Pełny tekst źródłaStone, Derrick. Walks, Tracks and Trails of Victoria. CSIRO Publishing, 2009. http://dx.doi.org/10.1071/9780643097919.
Pełny tekst źródłaRokison, Abigail. Shakespeare’s Dramatic Verse Line. Redaktor Jonathan Post. Oxford University Press, 2013. http://dx.doi.org/10.1093/oxfordhb/9780199607747.013.0024.
Pełny tekst źródłaSullivan, Sean G. Impulse Control Disorders in Medical Settings. Redaktorzy Jon E. Grant i Marc N. Potenza. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780195389715.013.0123.
Pełny tekst źródłaMeyer, Michel. The role of pathos: from argumentative responses to feeling and emotions. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199691821.003.0010.
Pełny tekst źródłaMoney, Jeannette. Comparative Immigration Policy. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190846626.013.380.
Pełny tekst źródłaThatamanil, John J. Circling the Elephant. Fordham University Press, 2020. http://dx.doi.org/10.5422/fordham/9780823288526.001.0001.
Pełny tekst źródłaOrtiz, Julian Arias, Raphaël Favory i Jean-Louis Vincent. Infection, sepsis, and multiorgan dysfunction syndrome. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199687039.003.0072.
Pełny tekst źródłaCzęści książek na temat "Short-time features"
Gómez, P., J. M. Ferrández, V. Rodellar, L. M. Mazaira i C. Muñoz. "Modeling Short-Time Parsing of Speech Features in Neocortical Structures". W Trends in Applied Intelligent Systems, 159–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13033-5_17.
Pełny tekst źródłaHerff, Christian, i Dean J. Krusienski. "Extracting Features from Time Series". W Fundamentals of Clinical Data Science, 85–100. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99713-1_7.
Pełny tekst źródłaGómez, V., A. Álvarez, P. Herrera, G. Castellanos i A. Orozco. "Short Time EEG Connectivity Features to Support Interpretability of MI Discrimination". W Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 699–706. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13469-3_81.
Pełny tekst źródłaSmith, Leslie S. "Extracting Features from the Short-term Time Structure of Cochlear Filtered Sound". W 4th Neural Computation and Psychology Workshop, London, 9–11 April 1997, 113–25. London: Springer London, 1998. http://dx.doi.org/10.1007/978-1-4471-1546-5_10.
Pełny tekst źródłaVelasquez-Martinez, F., A. M. Alvarez-Meza i G. Castellanos-Dominguez. "Connectivity Analysis of Motor Imagery Paradigm Using Short-Time Features and Kernel Similarities". W Artificial Computation in Biology and Medicine, 439–48. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18914-7_46.
Pełny tekst źródłaMorales, Juddy Y., Juan D. Castillo, Brayan M. León, Roberto Ferro Escobar i Andrés E. Gaona. "Audio Scene Classification Based on Convolutional Neural Networks: An Evaluation of Multiple Features and Topologies in Short Time Segments". W Lecture Notes in Electrical Engineering, 414–22. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-53021-1_42.
Pełny tekst źródłaWernhard, Christoph, i Wolfgang Bibel. "Learning from Łukasiewicz and Meredith: Investigations into Proof Structures". W Automated Deduction – CADE 28, 58–75. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79876-5_4.
Pełny tekst źródłaCerone, Antonio, i Graham Pluck. "A Formal Model for Emulating the Generation of Human Knowledge in Semantic Memory". W From Data to Models and Back, 104–22. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70650-0_7.
Pełny tekst źródłaZhan, Peng, Yupeng Hu, Wei Luo, Yang Xu, Qi Zhang i Xueqing Li. "Feature-based Online Segmentation Algorithm for Streaming Time Series (Short Paper)". W Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 477–87. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12981-1_33.
Pełny tekst źródłaNakanishi, Tomoko M. "Real-Time Water Movement in a Plant". W Novel Plant Imaging and Analysis, 39–72. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4992-6_2.
Pełny tekst źródłaStreszczenia konferencji na temat "Short-time features"
Sepulveda-Cano, L. M., A. M. Alvarez-Meza i G. Castellanos-Dominguez. "Training using short-time features for OSA discrimination". W 2012 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2012. http://dx.doi.org/10.1109/embc.2012.6345858.
Pełny tekst źródłaSyamanthika, Puppala, Tekkali Yogitha, Manche Kuruba Sai Hitha, Tiramareddy Manasa Swetha, S. S. Poorna i K. Anuraj. "Digit Identification from Speech using Short-Time Domain Features". W 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA). IEEE, 2020. http://dx.doi.org/10.1109/icirca48905.2020.9182788.
Pełny tekst źródłaTsiakoulis, Pirros, Alexandros Potamianos i Dimitrios Dimitriadis. "Short-time instantaneous frequency and bandwidth features for speech recognition". W Understanding (ASRU). IEEE, 2009. http://dx.doi.org/10.1109/asru.2009.5373305.
Pełny tekst źródłaKim, Bobae, Beomhee Jang, Donggeon Lee i Sungbin Im. "CNN-based UAV Detection with Short Time Fourier Transformed Acoustic Features". W 2020 International Conference on Electronics, Information, and Communication (ICEIC). IEEE, 2020. http://dx.doi.org/10.1109/iceic49074.2020.9051099.
Pełny tekst źródłaHuang, Huan, Natalie Baddour i Ming Liang. "Short-Time Kurtogram for Bearing Fault Feature Extraction Under Time-Varying Speed Conditions". W ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-85165.
Pełny tekst źródłaRizzi, A., M. Buccino, M. Panella i A. Uncini. "Optimal Short-Time Features for Music/Speech Classification of Compressed Audio Data". W 2006 International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06). IEEE, 2006. http://dx.doi.org/10.1109/cimca.2006.160.
Pełny tekst źródłaKai, Ding, Zhang Shigong, Zhang Kesheng i Lei Zhen. "Short-time and Spectrum Features of Noises Made by Vehicles for Recognition". W 2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE). IEEE, 2020. http://dx.doi.org/10.1109/auteee50969.2020.9315641.
Pełny tekst źródłaMohdiwale, Samrudhi, Tirath Prasad Sahu, Naresh Kumar Nagwani, Rahul Kumar Chaurasia i Shrish Verma. "Abnormal activity detection in forest reserve using cumulative short time fourier transform features". W 2017 International Conference on Intelligent Sustainable Systems (ICISS). IEEE, 2017. http://dx.doi.org/10.1109/iss1.2017.8389259.
Pełny tekst źródłaPinzon, Jaime D., i D. Graciela Colome. "Data Analytics of PMU Measurement Features for Real-time Short-term Voltage Stability Prediction". W 2019 FISE-IEEE/CIGRE Conference - Living the energy Transition (FISE/CIGRE). IEEE, 2019. http://dx.doi.org/10.1109/fisecigre48012.2019.8985004.
Pełny tekst źródłaNuhoglu, Mustafa Atahan. "Classification of radar signal features in electronic warfare with convolutional long-short time memory". W 2018 26th Signal Processing and Communications Applications Conference (SIU). IEEE, 2018. http://dx.doi.org/10.1109/siu.2018.8404452.
Pełny tekst źródłaRaporty organizacyjne na temat "Short-time features"
Berkowitz, Jacob, Nathan Beane, Kevin Philley, Nia Hurst i Jacob Jung. An assessment of long-term, multipurpose ecosystem functions and engineering benefits derived from historical dredged sediment beneficial use projects. Engineer Research and Development Center (U.S.), sierpień 2021. http://dx.doi.org/10.21079/11681/41382.
Pełny tekst źródłaDownes, Jane, red. Chalcolithic and Bronze Age Scotland: ScARF Panel Report. Society for Antiquaries of Scotland, wrzesień 2012. http://dx.doi.org/10.9750/scarf.09.2012.184.
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