Journal articles on the topic 'Linear perceptrons'
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Bylander, Tom. "Learning Linear Threshold Approximations Using Perceptrons." Neural Computation 7, no. 2 (March 1995): 370–79. http://dx.doi.org/10.1162/neco.1995.7.2.370.
Full textAlpaydin, E., and M. I. Jordan. "Local linear perceptrons for classification." IEEE Transactions on Neural Networks 7, no. 3 (May 1996): 788–94. http://dx.doi.org/10.1109/72.501737.
Full textBarber, D., D. Saad, and P. Sollich. "Test Error Fluctuations in Finite Linear Perceptrons." Neural Computation 7, no. 4 (July 1995): 809–21. http://dx.doi.org/10.1162/neco.1995.7.4.809.
Full textLegenstein, Robert, and Wolfgang Maass. "On the Classification Capability of Sign-Constrained Perceptrons." Neural Computation 20, no. 1 (January 2008): 288–309. http://dx.doi.org/10.1162/neco.2008.20.1.288.
Full textYu, Xin, Mian Xie, Li Xia Tang, and Chen Yu Li. "Learning Algorithm for Fuzzy Perceptron with Max-Product Composition." Applied Mechanics and Materials 687-691 (November 2014): 1359–62. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.1359.
Full textShah, J. V., and Chi-Sang Poon. "Linear independence of internal representations in multilayer perceptrons." IEEE Transactions on Neural Networks 10, no. 1 (1999): 10–18. http://dx.doi.org/10.1109/72.737489.
Full textZwietering, P. J., E. H. L. Aarts, and J. Wessels. "EXACT CLASSIFICATION WITH TWO-LAYERED PERCEPTRONS." International Journal of Neural Systems 03, no. 02 (January 1992): 143–56. http://dx.doi.org/10.1142/s0129065792000127.
Full textHara, Kazuyuki, and Masato Okada. "Ensemble Learning of Linear Perceptrons: On-Line Learning Theory." Journal of the Physical Society of Japan 74, no. 11 (November 15, 2005): 2966–72. http://dx.doi.org/10.1143/jpsj.74.2966.
Full textFrean, Marcus. "The Upstart Algorithm: A Method for Constructing and Training Feedforward Neural Networks." Neural Computation 2, no. 2 (June 1990): 198–209. http://dx.doi.org/10.1162/neco.1990.2.2.198.
Full textHamid, Danish, Syed Sajid Ullah, Jawaid Iqbal, Saddam Hussain, Ch Anwar ul Hassan, and Fazlullah Umar. "A Machine Learning in Binary and Multiclassification Results on Imbalanced Heart Disease Data Stream." Journal of Sensors 2022 (September 20, 2022): 1–13. http://dx.doi.org/10.1155/2022/8400622.
Full textBanda, Peter, Christof Teuscher, and Matthew R. Lakin. "Online Learning in a Chemical Perceptron." Artificial Life 19, no. 2 (April 2013): 195–219. http://dx.doi.org/10.1162/artl_a_00105.
Full textSollich, P. "Finite-size effects in learning and generalization in linear perceptrons." Journal of Physics A: Mathematical and General 27, no. 23 (December 7, 1994): 7771–84. http://dx.doi.org/10.1088/0305-4470/27/23/020.
Full textKatahira, Kentaro, Tatsuya Cho, Kazuo Okanoya, and Masato Okada. "Optimal node perturbation in linear perceptrons with uncertain eligibility trace." Neural Networks 23, no. 2 (March 2010): 219–25. http://dx.doi.org/10.1016/j.neunet.2009.11.013.
Full textChen, S., G. J. Gibson, C. F. N. Cowan, and P. M. Grant. "Adaptive equalization of finite non-linear channels using multilayer perceptrons." Signal Processing 20, no. 2 (June 1990): 107–19. http://dx.doi.org/10.1016/0165-1684(90)90122-f.
Full textVelásquez, Juan David, Fernán Alonso Villa, and Reinaldo C. Souza. "Time series forecasting using cascade correlation networks." Ingeniería e Investigación 30, no. 1 (January 1, 2010): 157–62. http://dx.doi.org/10.15446/ing.investig.v30n1.15226.
Full textZheng, Chun-Hou, De-Shuang Huang, Kang Li, George Irwin, and Zhan-Li Sun. "MISEP Method for Postnonlinear Blind Source Separation." Neural Computation 19, no. 9 (September 2007): 2557–78. http://dx.doi.org/10.1162/neco.2007.19.9.2557.
Full textDawson, Michael R. W., and Maya Gupta. "Probability matching in perceptrons: Effects of conditional dependence and linear nonseparability." PLOS ONE 12, no. 2 (February 17, 2017): e0172431. http://dx.doi.org/10.1371/journal.pone.0172431.
Full textHara, Kazuyuki, Yoichi Nakayama, Seiji Miyoshi, and Masato Okada. "Statistical Mechanics of On-Line Mutual Learning with Many Linear Perceptrons." Journal of the Physical Society of Japan 78, no. 11 (November 15, 2009): 114001. http://dx.doi.org/10.1143/jpsj.78.114001.
Full textGeibel, Peter, and Fritz Wysotzki. "Learning Perceptrons and Piecewise Linear Classifiers Sensitive to Example Dependent Costs." Applied Intelligence 21, no. 1 (July 2004): 45–56. http://dx.doi.org/10.1023/b:apin.0000027766.72235.bc.
Full textBarber, D., D. Saad, and P. Sollich. "Finite-size effects and optimal test set size in linear perceptrons." Journal of Physics A: Mathematical and General 28, no. 5 (March 7, 1995): 1325–34. http://dx.doi.org/10.1088/0305-4470/28/5/018.
Full textBaklagin, Nikolaevich Vyacheslav. "Selection of Parameters and Architecture of Multilayer Perceptrons for Predicting Ice Coverage of Lakes." Ekológia (Bratislava) 36, no. 3 (September 1, 2017): 226–34. http://dx.doi.org/10.1515/eko-2017-0019.
Full textErdogmus, D., O. Fontenla-Romero, J. C. Principe, A. Alonso-Betanzos, and E. Castillo. "Linear-Least-Squares Initialization of Multilayer Perceptrons Through Backpropagation of the Desired Response." IEEE Transactions on Neural Networks 16, no. 2 (March 2005): 325–37. http://dx.doi.org/10.1109/tnn.2004.841777.
Full textBack, Andrew D., and Ah Chung Tsoi. "An Adaptive Lattice Architecture for Dynamic Multilayer Perceptrons." Neural Computation 4, no. 6 (November 1992): 922–31. http://dx.doi.org/10.1162/neco.1992.4.6.922.
Full textBack, Andrew D., and Ah Chung Tsoi. "A Simplified Gradient Algorithm for IIR Synapse Multilayer Perceptrons." Neural Computation 5, no. 3 (May 1993): 456–62. http://dx.doi.org/10.1162/neco.1993.5.3.456.
Full textNABNEY, IAN T. "EFFICIENT TRAINING OF RBF NETWORKS FOR CLASSIFICATION." International Journal of Neural Systems 14, no. 03 (June 2004): 201–8. http://dx.doi.org/10.1142/s0129065704001930.
Full textAmari, Shun-ichi. "Natural Gradient Works Efficiently in Learning." Neural Computation 10, no. 2 (February 1, 1998): 251–76. http://dx.doi.org/10.1162/089976698300017746.
Full textCazé, Romain D., and Marcel Stimberg. "Neurons with dendrites can perform linearly separable computations with low resolution synaptic weights." F1000Research 9 (April 18, 2021): 1174. http://dx.doi.org/10.12688/f1000research.26486.3.
Full textCazé, Romain D., and Marcel Stimberg. "Neurons with dendrites can perform linearly separable computations with low resolution synaptic weights." F1000Research 9 (January 20, 2021): 1174. http://dx.doi.org/10.12688/f1000research.26486.2.
Full textCazé, Romain D., and Marcel Stimberg. "Dendritic neurons can perform linearly separable computations with low resolution synaptic weights." F1000Research 9 (September 28, 2020): 1174. http://dx.doi.org/10.12688/f1000research.26486.1.
Full textHayasaka, Taichi, Masashi Kitahara, and Shiro Usui. "On the Asymptotic Distribution of the Least-Squares Estimators in Unidentifiable Models." Neural Computation 16, no. 1 (January 1, 2004): 99–114. http://dx.doi.org/10.1162/08997660460734010.
Full textJohn Ohabuiro, Ugochukwu O. Matthew, Salisu Umar, Danladi Agadi Tonga, and Amaonwu Onyebuchi. "Global Solar Radiation Modelling using an Artificial Neural Network for Kazaure, Jigawa State, Nigeria." December 2022 4, no. 4 (January 21, 2023): 316–31. http://dx.doi.org/10.36548/jeea.2022.4.008.
Full textWu, Buchen, and Jiwei Qin. "A List-Ranking Framework Based on Linear and Non-Linear Fusion for Recommendation from Implicit Feedback." Entropy 24, no. 6 (May 31, 2022): 778. http://dx.doi.org/10.3390/e24060778.
Full textKhoshaim, Ahmed B., Essam B. Moustafa, Omar Talal Bafakeeh, and Ammar H. Elsheikh. "An Optimized Multilayer Perceptrons Model Using Grey Wolf Optimizer to Predict Mechanical and Microstructural Properties of Friction Stir Processed Aluminum Alloy Reinforced by Nanoparticles." Coatings 11, no. 12 (November 30, 2021): 1476. http://dx.doi.org/10.3390/coatings11121476.
Full textRoj, J. "Neural Network Based Real-time Correction of Transducer Dynamic Errors." Measurement Science Review 13, no. 6 (December 1, 2013): 286–91. http://dx.doi.org/10.2478/msr-2013-0042.
Full textLuna, Antonio Madueño, Miriam López Lineros, Javier Estévez Gualda, Juan Vicente Giráldez Cervera, and José Miguel Madueño Luna. "Assessing the Best Gap-Filling Technique for River Stage Data Suitable for Low Capacity Processors and Real-Time Application Using IoT." Sensors 20, no. 21 (November 7, 2020): 6354. http://dx.doi.org/10.3390/s20216354.
Full textLegenstein, Robert, Christian Naeger, and Wolfgang Maass. "What Can a Neuron Learn with Spike-Timing-Dependent Plasticity?" Neural Computation 17, no. 11 (November 1, 2005): 2337–82. http://dx.doi.org/10.1162/0899766054796888.
Full textKerlirzin, P., and P. Refregier. "Theoretical investigation of the robustness of multilayer perceptrons: analysis of the linear case and extension to nonlinear networks." IEEE Transactions on Neural Networks 6, no. 3 (May 1995): 560–71. http://dx.doi.org/10.1109/72.377963.
Full textTsaptsinos, D., and J. R. Leigh. "Modelling of a fermentation process using Multi-Layer Perceptrons: Epochs vs Pattern learning, Sigmoid vs Linear transfer function." Journal of Microcomputer Applications 16, no. 2 (April 1993): 125–36. http://dx.doi.org/10.1006/jmca.1993.1011.
Full textBarnawi, Abdulaziz Y., and Ismail M. Keshta. "Energy Management in Wireless Sensor Networks Based on Naive Bayes, MLP, and SVM Classifications: A Comparative Study." Journal of Sensors 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/6250319.
Full textCoutinho, Eluã Ramos, Robson Mariano Silva, and Angel Ramon Sanchez Delgado. "Utilização de Técnicas de Inteligência Computacional na Predição de Dados Meteorológicos." Revista Brasileira de Meteorologia 31, no. 1 (March 2016): 24–36. http://dx.doi.org/10.1590/0102-778620140115.
Full textSilva, Cecilia Cordeiro da, Clarisse Lins de Lima, Ana Clara Gomes da Silva, Giselle Machado Magalhães Moreno, Anwar Musah, Aisha Aldosery, Livia Dutra, et al. "Forecasting Dengue, Chikungunya and Zika cases in Recife, Brazil: a spatio-temporal approach based on climate conditions, health notifications and machine learning." Research, Society and Development 10, no. 12 (September 26, 2021): e452101220804. http://dx.doi.org/10.33448/rsd-v10i12.20804.
Full textSAKURAI, AKITO. "A FAST AND CONVERGENT STOCHASTIC MLP LEARNING ALGORITHM." International Journal of Neural Systems 11, no. 06 (December 2001): 573–83. http://dx.doi.org/10.1142/s0129065701000977.
Full textXU, LEI, STAN KLASA, and ALAN YUILLE. "RECENT ADVANCES ON TECHNIQUES OF STATIC FEEDFORWARD NETWORKS WITH SUPERVISED LEARNING." International Journal of Neural Systems 03, no. 03 (January 1992): 253–90. http://dx.doi.org/10.1142/s0129065792000218.
Full textKarras, D. A., and B. G. Mertzios. "Time series modeling of endocardial border motion in ultrasonic images comparing support vector machines, multilayer perceptrons and linear estimation techniques." Measurement 36, no. 3-4 (October 2004): 331–45. http://dx.doi.org/10.1016/j.measurement.2004.09.012.
Full textFarrell, Max H., Tengyuan Liang, and Sanjog Misra. "Deep Neural Networks for Estimation and Inference." Econometrica 89, no. 1 (2021): 181–213. http://dx.doi.org/10.3982/ecta16901.
Full textTsuchida, Russell, Tim Pearce, Chris Van der Heide, Fred Roosta, and Marcus Gallagher. "Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 11 (May 18, 2021): 9967–77. http://dx.doi.org/10.1609/aaai.v35i11.17197.
Full textSRIRAAM, N., and C. ESWARAN. "EEG SIGNAL COMPRESSION USING RADIAL BASIS NEURAL NETWORKS." Journal of Mechanics in Medicine and Biology 04, no. 02 (June 2004): 143–52. http://dx.doi.org/10.1142/s0219519404000928.
Full textKUTSCHENREITER-PRASZKIEWICZ, Izabela. "MACHINE LEARNING IN SMED." Journal of Machine Engineering 18, no. 2 (June 12, 2018): 31–40. http://dx.doi.org/10.5604/01.3001.0012.0923.
Full textGHOSH, JOYDEEP, and YOAN SHIN. "EFFICIENT HIGHER-ORDER NEURAL NETWORKS FOR CLASSIFICATION AND FUNCTION APPROXIMATION." International Journal of Neural Systems 03, no. 04 (January 1992): 323–50. http://dx.doi.org/10.1142/s0129065792000255.
Full textSUYKENS, JOHAN A. K., JOOS VANDEWALLE, and BART DE MOOR. "INTELLIGENCE AND COOPERATIVE SEARCH BY COUPLED LOCAL MINIMIZERS." International Journal of Bifurcation and Chaos 11, no. 08 (August 2001): 2133–44. http://dx.doi.org/10.1142/s0218127401003371.
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