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FPGA Implementation of Neurocomputational Models: Comparison Between Standard Back-Propagation and C-Mantec Constructive Algorithm., , , и . Neural Process. Lett., 46 (3): 899-914 (2017)Red-Black Tree Based NeuroEvolution of Augmenting Topologies., , , , и . IWANN (2), том 11507 из Lecture Notes in Computer Science, стр. 678-686. Springer, (2019)Smart motion detection sensor based on video processing using self-organizing maps., , , и . Expert Syst. Appl., (2016)Layer multiplexing FPGA implementation for deep back-propagation learning., , , и . Integr. Comput. Aided Eng., 24 (2): 171-185 (2017)Exploratory Data Analysis and Foreground Detection with the Growing Hierarchical Neural Forest., , , и . Neural Process. Lett., 52 (3): 2537-2563 (2020)Thermal comfort estimation using a neurocomputational model., , , , и . LA-CCI, стр. 1-5. IEEE, (2016)Prediction of Learning Improvement in Mathematics through a Video Game using Neurocomputational Models., , , и . ICAART (2), стр. 554-559. SciTePress, (2019)FPGA Implementation Comparison Between C-Mantec and Back-Propagation Neural Network Algorithms., , , и . IWANN (2), том 9095 из Lecture Notes in Computer Science, стр. 197-208. Springer, (2015)Solving Scheduling Problems with Genetic Algorithms Using a Priority Encoding Scheme., , , , , , и . IWANN (1), том 10305 из Lecture Notes in Computer Science, стр. 52-61. Springer, (2017)Unsupervised learning by cluster quality optimization., , и . Inf. Sci., (2018)