Literatura científica selecionada sobre o tema "Analog-to-feature converter"
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Artigos de revistas sobre o assunto "Analog-to-feature converter"
Back, Antoine, Paul Chollet, Olivier Fercoq e Patricia Desgreys. "Power-aware feature selection for optimized Analog-to-Feature converter". Microelectronics Journal 122 (abril de 2022): 105386. http://dx.doi.org/10.1016/j.mejo.2022.105386.
Texto completo da fonteAgarwal, Ritika, e Sameer Sonkusale. "Input-Feature Correlated Asynchronous Analog to Information Converter for ECG Monitoring". IEEE Transactions on Biomedical Circuits and Systems 5, n.º 5 (outubro de 2011): 459–67. http://dx.doi.org/10.1109/tbcas.2011.2116787.
Texto completo da fonteZhao, Ying Kai, Liang Yin, Zhao Tong Liu, Wei Ping Chen e Xiao Wei Liu. "A 16 Bits 500 kHz Sigma-Delta DAC for Silicon Micro Gyroscope". Key Engineering Materials 645-646 (maio de 2015): 605–9. http://dx.doi.org/10.4028/www.scientific.net/kem.645-646.605.
Texto completo da fonteManokhin, Mikhail, Paul Chollet e Patricia Desgreys. "Towards Flexible and Low-Power Wireless Smart Sensors: Reconfigurable Analog-to-Feature Conversion for Healthcare Applications". Sensors 24, n.º 3 (3 de fevereiro de 2024): 999. http://dx.doi.org/10.3390/s24030999.
Texto completo da fonteTriwiyanto, T., Endro Yulianto, I. Dewa Gede Hari Wisana, Muhammad Ridha Mak’ruf, Bambang Guruh Irianto, Endang Dian Setioningsih, Ridho Hanggara Mukti e Dhimas Sugma Herdinanta. "Electromyography Feature Analysis to Recognize the Hand Motion in a Prosthetic Hand Design". Journal of Biomimetics, Biomaterials and Biomedical Engineering 50 (abril de 2021): 25–37. http://dx.doi.org/10.4028/www.scientific.net/jbbbe.50.25.
Texto completo da fonteSahu, Anil Kumar, Vivek Kumar Chandra e G. R. Sinha. "Analysis of Quantization Noise and Power Estimation of Continuous-Time Delta Sigma Analog-to-Digital Converter Using Test Enable Feature For 4G Radios". International Journal of Informatics and Communication Technology (IJ-ICT) 7, n.º 2 (1 de agosto de 2018): 82. http://dx.doi.org/10.11591/ijict.v7i2.pp82-88.
Texto completo da fonteVan den Bossche, Alex, Ekaterina Dimitrova, Vencislav Valchev e Firgan Feradov. "A simplified controller and detailed dynamics of constant off-time peak current control". Journal of Electrical Engineering 68, n.º 5 (1 de setembro de 2017): 390–95. http://dx.doi.org/10.1515/jee-2017-0072.
Texto completo da fonteKim, Keonwook, e Yujin Hong. "Gaussian Process Regression for Single-Channel Sound Source Localization System Based on Homomorphic Deconvolution". Sensors 23, n.º 2 (9 de janeiro de 2023): 769. http://dx.doi.org/10.3390/s23020769.
Texto completo da fonteYeh, Yun Chi, Tsung Fu Chien, Cheng Yuan Chang e Tsui Shiun Chu. "A Mahalanobis Distance Measurement Method to Analyze Current Waveform for Determining the Motor’s Quality Types". Applied Mechanics and Materials 870 (setembro de 2017): 317–22. http://dx.doi.org/10.4028/www.scientific.net/amm.870.317.
Texto completo da fonteFang, Ni, Dong Wang, Xiangming Sun, Chaosong Gao, Ran Chen, Zhuo Zhou, Shiqiang Zhou, Cheng Lian e Zijian Lang. "50.3 ps time resolution and an 11-channel time measuring chip for Topmetal detectors". Journal of Instrumentation 19, n.º 03 (1 de março de 2024): C03047. http://dx.doi.org/10.1088/1748-0221/19/03/c03047.
Texto completo da fonteTeses / dissertações sobre o assunto "Analog-to-feature converter"
Back, Antoine. "Conception et intégration d'un convertisseur analogique-paramètres flexible pour les capteurs intelligents". Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAT020.
Texto completo da fonteThe Internet of Things (IoT) is currently experiencing huge developments. IoT includes lots of different devices such as Wireless Sensors Networks (WSN) or wearable electronics that rely on wireless communications. These networks need to understand the context in which they are used. This mean that the system must know what is happening around it, i.e. sense the environment, and understands the needs of the user. This requires always-on sensing on many sensors while being small, cheap, reliable and having a lifetime of several years. Analog-to-Feature (A2F) conversion is a new acquisition method that was thought for IoT devices. The converter aims at extracting useful features directly on the analog signal. By carefully choosing a set of features, it is possible to acquire only the relevant information for a given task. The proposed converter is based on the Non-Uniform Wavelet Sampling (NUWS) architecture. The architecture mixes the analog signal with tunable wavelets prior to integration and digital conversion. The aim of the thesis is to propose a method to design a generic A2F converter based on the NUWS. It includes the definition of the wavelet parameters in order to acquire a broad range of low frequency signals (ECG, EMG, EEG, speech …). This step requires the use of feature selection algorithms and machine learning algorithms for selecting the best set of wavelets for a given application and should be used to define the specifications for the converter. The feature selection step must be aware of physical implementation constraints to optimize energy consumption as much as possible. A feature selection algorithm is proposed to choose wavelets for a given application, in order to maximize classification accuracy while decreasing power consumption, through a power model designed in CMOS 0.18μm
Livros sobre o assunto "Analog-to-feature converter"
Piepenburg, Scott. Digitizing Audiovisual and Nonprint Materials. ABC-CLIO, LLC, 2015. http://dx.doi.org/10.5040/9798400640674.
Texto completo da fonteCapítulos de livros sobre o assunto "Analog-to-feature converter"
Octavian Nemeș, Raul, Mircea Ruba, Sorina Maria Ciornei e Raluca Maria Raia. "Powerful Multilevel Simulation Tool for HiL Analysis of Urban Electric vehicle’s Propulsion Systems". In New Perspectives on Electric Vehicles [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.98532.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Analog-to-feature converter"
Back, Antoine, Paul Chollet, Olivier Fercoq e Patricia Desgreys. "Feature selection algorithms for flexible analog-to-feature converter". In 2020 18th IEEE International New Circuits and Systems Conference (NEWCAS). IEEE, 2020. http://dx.doi.org/10.1109/newcas49341.2020.9159817.
Texto completo da fonteManokhin, Mikhail, Paul Chollet e Patricia Desgreys. "Flexible Analog-to-Feature Converter for Wireless Smart Healthcare Sensors". In 2023 21st IEEE Interregional NEWCAS Conference (NEWCAS). IEEE, 2023. http://dx.doi.org/10.1109/newcas57931.2023.10198150.
Texto completo da fonteTang, Xiaochen, Shanshan Liu, Wenjie Che e Wei Tang. "Tampering Attack Detection in Analog to Feature Converter for Wearable Biosensor". In 2022 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2022. http://dx.doi.org/10.1109/iscas48785.2022.9937707.
Texto completo da fonteTang, Xiaochen, Qisong Hu e Wei Tang. "Analog to Digital Feature Converter based on Oversampling Modulators for ECG Delineation". In 2019 IEEE 62nd International Midwest Symposium on Circuits and Systems (MWSCAS). IEEE, 2019. http://dx.doi.org/10.1109/mwscas.2019.8885145.
Texto completo da fontedel Campo, Sergio Martin, Kim Albertsson, Joakim Nilsson, Jens Eliasson e Fredrik Sandin. "FPGA prototype of machine learning analog-to-feature converter for event-based succinct representation of signals". In 2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP). IEEE, 2013. http://dx.doi.org/10.1109/mlsp.2013.6661996.
Texto completo da fonteChakrabartty, Shantanu. "Multiple-input multiple-output (MIMO) analog-to-feature converter chipsets for sub-wavelength acoustic source localization and bearing estimation". In SPIE Defense, Security, and Sensing, editado por Edward M. Carapezza. SPIE, 2010. http://dx.doi.org/10.1117/12.852671.
Texto completo da fonteSwope, C. H., J. G. Link e D. G. Haugen. "Multichannel optical system for a medical diagnostic analyzer". In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/oam.1992.thv4.
Texto completo da fonteGuo, Chencheng, Hui Qian e Baoling Hong. "Feature-Based Sensing Matrix Design for Analog to Information Converters". In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022. http://dx.doi.org/10.1109/icassp43922.2022.9747114.
Texto completo da fonteChakrabartty, Shantanu, e Amit Gore. "Sigma-delta analog to LPC feature converters for portable recognition interfaces". In 2009 IEEE International Symposium on Circuits and Systems - ISCAS 2009. IEEE, 2009. http://dx.doi.org/10.1109/iscas.2009.5118352.
Texto completo da fonteSleiman, Nicolas, e Julie A. Reyer. "HIL Simulation of a Track Type Tractor for Autonomous Controller Testing". In ASME 2008 Dynamic Systems and Control Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/dscc2008-2210.
Texto completo da fonte