Auswahl der wissenschaftlichen Literatur zum Thema „Analog-to-feature converter“
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Zeitschriftenartikel zum Thema "Analog-to-feature converter"
Back, Antoine, Paul Chollet, Olivier Fercoq und Patricia Desgreys. „Power-aware feature selection for optimized Analog-to-Feature converter“. Microelectronics Journal 122 (April 2022): 105386. http://dx.doi.org/10.1016/j.mejo.2022.105386.
Der volle Inhalt der QuelleAgarwal, Ritika, und Sameer Sonkusale. „Input-Feature Correlated Asynchronous Analog to Information Converter for ECG Monitoring“. IEEE Transactions on Biomedical Circuits and Systems 5, Nr. 5 (Oktober 2011): 459–67. http://dx.doi.org/10.1109/tbcas.2011.2116787.
Der volle Inhalt der QuelleZhao, Ying Kai, Liang Yin, Zhao Tong Liu, Wei Ping Chen und Xiao Wei Liu. „A 16 Bits 500 kHz Sigma-Delta DAC for Silicon Micro Gyroscope“. Key Engineering Materials 645-646 (Mai 2015): 605–9. http://dx.doi.org/10.4028/www.scientific.net/kem.645-646.605.
Der volle Inhalt der QuelleManokhin, Mikhail, Paul Chollet und Patricia Desgreys. „Towards Flexible and Low-Power Wireless Smart Sensors: Reconfigurable Analog-to-Feature Conversion for Healthcare Applications“. Sensors 24, Nr. 3 (03.02.2024): 999. http://dx.doi.org/10.3390/s24030999.
Der volle Inhalt der QuelleTriwiyanto, T., Endro Yulianto, I. Dewa Gede Hari Wisana, Muhammad Ridha Mak’ruf, Bambang Guruh Irianto, Endang Dian Setioningsih, Ridho Hanggara Mukti und Dhimas Sugma Herdinanta. „Electromyography Feature Analysis to Recognize the Hand Motion in a Prosthetic Hand Design“. Journal of Biomimetics, Biomaterials and Biomedical Engineering 50 (April 2021): 25–37. http://dx.doi.org/10.4028/www.scientific.net/jbbbe.50.25.
Der volle Inhalt der QuelleSahu, Anil Kumar, Vivek Kumar Chandra und 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, Nr. 2 (01.08.2018): 82. http://dx.doi.org/10.11591/ijict.v7i2.pp82-88.
Der volle Inhalt der QuelleVan den Bossche, Alex, Ekaterina Dimitrova, Vencislav Valchev und Firgan Feradov. „A simplified controller and detailed dynamics of constant off-time peak current control“. Journal of Electrical Engineering 68, Nr. 5 (01.09.2017): 390–95. http://dx.doi.org/10.1515/jee-2017-0072.
Der volle Inhalt der QuelleKim, Keonwook, und Yujin Hong. „Gaussian Process Regression for Single-Channel Sound Source Localization System Based on Homomorphic Deconvolution“. Sensors 23, Nr. 2 (09.01.2023): 769. http://dx.doi.org/10.3390/s23020769.
Der volle Inhalt der QuelleYeh, Yun Chi, Tsung Fu Chien, Cheng Yuan Chang und Tsui Shiun Chu. „A Mahalanobis Distance Measurement Method to Analyze Current Waveform for Determining the Motor’s Quality Types“. Applied Mechanics and Materials 870 (September 2017): 317–22. http://dx.doi.org/10.4028/www.scientific.net/amm.870.317.
Der volle Inhalt der QuelleFang, Ni, Dong Wang, Xiangming Sun, Chaosong Gao, Ran Chen, Zhuo Zhou, Shiqiang Zhou, Cheng Lian und Zijian Lang. „50.3 ps time resolution and an 11-channel time measuring chip for Topmetal detectors“. Journal of Instrumentation 19, Nr. 03 (01.03.2024): C03047. http://dx.doi.org/10.1088/1748-0221/19/03/c03047.
Der volle Inhalt der QuelleDissertationen zum Thema "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.
Der volle Inhalt der QuelleThe 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
Bücher zum Thema "Analog-to-feature converter"
Piepenburg, Scott. Digitizing Audiovisual and Nonprint Materials. ABC-CLIO, LLC, 2015. http://dx.doi.org/10.5040/9798400640674.
Der volle Inhalt der QuelleBuchteile zum Thema "Analog-to-feature converter"
Octavian Nemeș, Raul, Mircea Ruba, Sorina Maria Ciornei und 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.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Analog-to-feature converter"
Back, Antoine, Paul Chollet, Olivier Fercoq und 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.
Der volle Inhalt der QuelleManokhin, Mikhail, Paul Chollet und 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.
Der volle Inhalt der QuelleTang, Xiaochen, Shanshan Liu, Wenjie Che und 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.
Der volle Inhalt der QuelleTang, Xiaochen, Qisong Hu und 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.
Der volle Inhalt der Quelledel Campo, Sergio Martin, Kim Albertsson, Joakim Nilsson, Jens Eliasson und 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.
Der volle Inhalt der QuelleChakrabartty, 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, herausgegeben von Edward M. Carapezza. SPIE, 2010. http://dx.doi.org/10.1117/12.852671.
Der volle Inhalt der QuelleSwope, C. H., J. G. Link und 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.
Der volle Inhalt der QuelleGuo, Chencheng, Hui Qian und 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.
Der volle Inhalt der QuelleChakrabartty, Shantanu, und 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.
Der volle Inhalt der QuelleSleiman, Nicolas, und 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.
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