Literatura académica sobre el tema "Binary output"
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Artículos de revistas sobre el tema "Binary output"
Anashin, Vladimir. "Discreteness causes waves". Facta universitatis - series: Physics, Chemistry and Technology 14, n.º 3 (2016): 143–96. http://dx.doi.org/10.2298/fupct1603143a.
Texto completoMoreno, E. G., B. Iniguez, M. Roca, J. Segura y S. Sureda. "CMOS radiation sensor with binary output". IEEE Transactions on Nuclear Science 42, n.º 3 (junio de 1995): 174–78. http://dx.doi.org/10.1109/23.387358.
Texto completoYum, Bong-Jin y Seong-Jun Kim. "On parameter design of binary-input-and-binary-output dynamic systems". Quality and Reliability Engineering International 9, n.º 6 (noviembre de 1993): 471–76. http://dx.doi.org/10.1002/qre.4680090603.
Texto completoYang, Sibo, Shusheng Wang, Lanyin Sun, Zhongxuan Luo y Yuan Bao. "Output Layer Structure Optimization for Weighted Regularized Extreme Learning Machine Based on Binary Method". Symmetry 15, n.º 1 (16 de enero de 2023): 244. http://dx.doi.org/10.3390/sym15010244.
Texto completoGurevich, Yuri y Saharon Shelah. "Time polynomial in input or output". Journal of Symbolic Logic 54, n.º 3 (septiembre de 1989): 1083–88. http://dx.doi.org/10.2307/2274767.
Texto completoXue, Aijun y Xiaodan Wang. "Cost-sensitive design of error correcting output codes". Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 232, n.º 10 (12 de mayo de 2017): 1871–81. http://dx.doi.org/10.1177/0954406217709303.
Texto completoRen, Xiao Guang, Yu Hua Tang y Xin Hai Xu. "Format Optimization for Periodical Snapshot Output in CFD Simulation". Applied Mechanics and Materials 457-458 (octubre de 2013): 910–18. http://dx.doi.org/10.4028/www.scientific.net/amm.457-458.910.
Texto completoPÉREZ ARCILA, MAURICIO y MARTIN ALONSO TAMAYO VELEZ. "IMPLEMENTATION OF LEBESGUE SAMPLING METHOD AND DIGITAL SENSORS FOR CONTROLLING THE LEVEL VARIABLE IN A CONTINUOUS SYSTEM". DYNA NEW TECHNOLOGIES 8, n.º 1 (11 de noviembre de 2021): [14 P.]. http://dx.doi.org/10.6036/nt10248.
Texto completoSilva, Carla, Ana Aguiar y Inês Dutra. "Quantum Binary Classification (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 18 (18 de mayo de 2021): 15889–90. http://dx.doi.org/10.1609/aaai.v35i18.17941.
Texto completoRahmadhany, Sri. "IDENTIFIKASI POLA KARAKTER ANAK DENGAN ALGORITMA PERCEPTRON". JURNAL TEKNOLOGI INFORMASI 3, n.º 1 (13 de junio de 2019): 86. http://dx.doi.org/10.36294/jurti.v3i1.695.
Texto completoTesis sobre el tema "Binary output"
Grama, Keshava. "Binary matrix for pedestrian tracking in infrared images". Thesis, Edinburgh Napier University, 2013. http://researchrepository.napier.ac.uk/Output/6153.
Texto completoChapin, Patrick Samuel. "Analysis of experiments to validate computer models with binary output". [Ames, Iowa : Iowa State University], 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3389285.
Texto completoOzkan, Ugur. "Application of the constrained implicants set concept to the minimization of binary functions". Thesis, Monterey, California : Naval Postgraduate School, 1990. http://handle.dtic.mil/100.2/ADA239470.
Texto completoThesis Advisor(s): Yang, Chyan ; Butler, Jon T. "September 1990." Description based on title screen as viewed on March 22, 2010. Author(s) subject terms: Constrained Implicants Set Concept, Binary Minimization. Includes bibliographical references (p. 75-76). Also available in print.
Oualla, Hicham. "Contributions à l'identification en boucle ouverte/fermée des systèmes à base de données binaires". Electronic Thesis or Diss., Normandie, 2022. http://www.theses.fr/2022NORMC229.
Texto completoThis thesis is devoted to the identification of systems based on binary data. First, a brief presentation of all the methods of identification of systems based on the use of binary data existing in the literature is given. In the following, we are interested in the problem of open loop identification of systems with binary output and input. We propose methods for the identification of FIR systems and more complex IIR systems with binary input and output. These methods are analyzed and tested by numerical examples. In the rest of this work, we propose first solutions to the problems of closed-loop identification of systems based on binary data. The first solutions are dedicated to binary output systems, the closed loop excitation is assumed to be high resolution. Finally, two methods are proposed for closed loop systems with binary output and input. These solutions are tested on numerical examples to quantify their performances
Ataman, Kaan. "Learning to rank by maximizing the AUC with linear programming for problems with binary output". Diss., University of Iowa, 2007. http://ir.uiowa.edu/etd/151.
Texto completoChaudhari, Pragat. "Analytical Methods for the Performance Evaluation of Binary Linear Block Codes". Thesis, University of Waterloo, 2000. http://hdl.handle.net/10012/904.
Texto completoMedvedieva, S. O., I. V. Bogach, V. A. Kovenko, С. О. Медведєва, І. В. Богач y В. А. Ковенко. "Neural networks in Machine learning". Thesis, ВНТУ, 2019. http://ir.lib.vntu.edu.ua//handle/123456789/24788.
Texto completoThe paper covers the basic principles of Neural Networks’ work. Special attention is paid to Frank Rosenblatt’s model of the network called “perceptron”. In addition, the article touches upon the main programming languages used to write software for Neural Networks.
FALEH, MOHAMAD SALEH. "Conception, realisation et caracterisation de transistors bipolaires de puissance a heterojonction gainp/gaas et comparaison avec les tbh's gaalas/gaas". Toulouse 3, 1998. http://www.theses.fr/1998TOU30027.
Texto completoHui-LiangYu y 游輝亮. "Dual Path Binary Neural Network with Adaptive Output Range". Thesis, 2018. http://ndltd.ncl.edu.tw/handle/nuydfp.
Texto completo國立成功大學
資訊工程學系
106
In recent years, deep neural networks (DNNs) have achieved state-of-the-art results in the fields of image recognition, semantic segmentation and machine translation. However, powerful DNNs usually have a large number of parameters and complex calculations. For instance, ImageNet classification challenge winner in 2012, Alex Net, has a model size of about 249MB and 60 million parameters, which needs to perform about 1.5 billion FLOPs to classify a 224 x 224 image. While perform such complex computations, GPUs based machines usually used to speed up training process and inference time. However, for embedded devices, such as smart phones or Internet of Things, there is only a small amount of memory, battery power and computing resources, so it is difficult to deploy DNN to these devices. In the field of model compression, the binary neural network (BNN) is a very promising method, which features are low power consumption and low storage usage, but there is a large gap in prediction accuracy compared with full-precision networks. This thesis proposed a BNN that about the same storage usage as other BNNs and prediction accuracy is close to full-precision network. The method proposed in this thesis has three characteristics: First, the convolution layers have two input sources by dual path method. Second, round the batch normalization output. Third, adjust each layer output by a trainable parameter. The experiments show, our model size is about equal to other BNNs, but the prediction accuracy is much higher. In CIFAR-10 dataset, the prediction accuracy is at least 2.85% higher than other BNNs, even better than ternary network, only 0.69% loss compared to full-precision network. In SVHN dataset, the prediction accuracy is at least 0.21% higher than other BNNs, and even more than 0.58% compared to full-precision network.
"Analysis of experiments to validate computer models with binary output". IOWA STATE UNIVERSITY, 2010. http://pqdtopen.proquest.com/#viewpdf?dispub=3389285.
Texto completoLibros sobre el tema "Binary output"
Behrooz, Anahit. Mapping Middle-earth. Bloomsbury Publishing Plc, 2024. http://dx.doi.org/10.5040/9781350290792.
Texto completoNakai, You. Reminded by the Instruments. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780190686765.001.0001.
Texto completoHoste, Eric A. J., John A. Kellum y Norbert Lameire. Definitions, classification, epidemiology, and risk factors of acute kidney injury. Editado por Norbert Lameire. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199592548.003.0220_update_001.
Texto completoKhatun, Samia. Australianama. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780190922603.001.0001.
Texto completoCapítulos de libros sobre el tema "Binary output"
Ye, Tao y Xuefeng Zhu. "Binary Coded Output Support Vector Machine". En Intelligent Computing Theories and Technology, 47–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39482-9_6.
Texto completoBabu, Hafiz Md Hasan. "Multiple-Valued Input Binary-Valued Output Functions". En VLSI Circuits and Embedded Systems, 107–20. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003269182-11.
Texto completoSun, Qilin, Yan Liu, Zhengxue Li, Sibo Yang, Wei Wu y Jiuwu Jin. "The Binary Output Units of Neural Network". En Advances in Neural Networks – ISNN 2013, 250–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39065-4_31.
Texto completoLaisney, François, Michael Lechner y Winfried Pohlmeier. "Semi-Nonparametric Estimation of Binary Choice Models Using Panel Data: An Application to the Innovative Activity of German Firms". En Output and Employment Fluctuations, 87–101. Heidelberg: Physica-Verlag HD, 1994. http://dx.doi.org/10.1007/978-3-642-57989-9_7.
Texto completoMorvai, Gusztáv. "Guessing the Output of a Stationary Binary Time Series". En Contributions to Statistics, 207–15. Heidelberg: Physica-Verlag HD, 2003. http://dx.doi.org/10.1007/978-3-642-57410-8_18.
Texto completoLin, Yi, Lucas M. Tabajara y Moshe Y. Vardi. "ZDD Boolean Synthesis". En Tools and Algorithms for the Construction and Analysis of Systems, 64–83. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99524-9_4.
Texto completoSchirmer, Pascal A. y Iosif Mporas. "Binary versus Multiclass Deep Learning Modelling in Energy Disaggregation". En Springer Proceedings in Energy, 45–51. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63916-7_6.
Texto completoGalán, Gerhard y Juris Muñoz. "A new input-output function for binary hopfield neural networks". En Lecture Notes in Computer Science, 311–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/bfb0098187.
Texto completoBelfiore, J. C. "A weighted-output symbol-by-symbol decoding algorithm of binary convolutional codes". En Coding Theory and Applications, 154–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/3-540-19368-5_17.
Texto completoChaudhari, Narendra S. y Aruna Tiwari. "Extension of Binary Neural Networks for Multi-class Output and Finite Automata". En Neural Information Processing: Research and Development, 211–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-39935-3_12.
Texto completoActas de conferencias sobre el tema "Binary output"
Guo, Zhixia, Sitao Li, Jiaxiong Ye, Ruan Yu, Qiyang Xu y Guoping Zhang. "Binary optical resonator with flattop output". En Optical Systems Design and Production, editado por Fritz Merkle. SPIE, 1999. http://dx.doi.org/10.1117/12.360043.
Texto completoMoskowitz, Ira S., Paul Cotae, Pedro N. Safier y Daniel L. Kang. "Capacity bounds and stochastic resonance for binary input binary output channels". En 2012 Computing, Communications and Applications Conference (ComComAp). IEEE, 2012. http://dx.doi.org/10.1109/comcomap.2012.6154003.
Texto completoShari, Shahrouz, A. Korhan Tanc y Tolga M. Duman. "LDPC code design for binary-input binary-output Z interference channels". En 2015 IEEE International Symposium on Information Theory (ISIT). IEEE, 2015. http://dx.doi.org/10.1109/isit.2015.7282622.
Texto completoQian, Jing, Feifei Gao, Shi Jin, Ling Xing y Junhui Zhao. "Capacity of Ambient Backscatter Communications with Binary Input and Binary Output Channel". En GLOBECOM 2018 - 2018 IEEE Global Communications Conference. IEEE, 2018. http://dx.doi.org/10.1109/glocom.2018.8647136.
Texto completoMoskowitz, Ira S., Paul Cotae y Pedro N. Safier. "Algebraic information theory and stochastic resonance for binary-input binary-output channels". En 2012 46th Annual Conference on Information Sciences and Systems (CISS). IEEE, 2012. http://dx.doi.org/10.1109/ciss.2012.6310786.
Texto completoSwanson, Gary J., James R. Leger y Wilfrid B. Veldkamp. "Tandem Binary Structures for Increased Coupling Efficiency of Laser Beams". En Holography. Washington, D.C.: Optica Publishing Group, 1986. http://dx.doi.org/10.1364/holography.1986.tud5.
Texto completoCao, Jun y Huimin Ma. "Regression-based parameter optimization for binary output systems". En 2015 3rd International Conference on Information and Communication Technology (ICoICT ). IEEE, 2015. http://dx.doi.org/10.1109/icoict.2015.7231473.
Texto completoYue, Tinghai. "The characterizations of binary vector-output plateaued functions". En 2010 IEEE International Conference on Wireless Communications, Networking and Information Security (WCNIS). IEEE, 2010. http://dx.doi.org/10.1109/wcins.2010.5541807.
Texto completoYue, Tinghai. "A construction of binary vector-output plateaued functions". En 2010 IEEE International Conference on Wireless Communications, Networking and Information Security (WCNIS). IEEE, 2010. http://dx.doi.org/10.1109/wcins.2010.5541808.
Texto completoNguyen, Thuan y Thinh Nguyen. "Structure of Optimal Quantizer for Binary-Input Continuous-Output Channels with Output Constraints". En 2020 IEEE International Symposium on Information Theory (ISIT). IEEE, 2020. http://dx.doi.org/10.1109/isit44484.2020.9174174.
Texto completoInformes sobre el tema "Binary output"
Farhi, Edward y Hartmut Neven. Classification with Quantum Neural Networks on Near Term Processors. Web of Open Science, diciembre de 2020. http://dx.doi.org/10.37686/qrl.v1i2.80.
Texto completoSinclair, Samantha y Sally Shoop. Automated detection of austere entry landing zones : a “GRAIL Tools” validation assessment. Engineer Research and Development Center (U.S.), agosto de 2022. http://dx.doi.org/10.21079/11681/45265.
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