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FPGA Implementation of Neurocomputational Models: Comparison Between Standard Back-Propagation and C-Mantec Constructive Algorithm., , , and . Neural Process. Lett., 46 (3): 899-914 (2017)Red-Black Tree Based NeuroEvolution of Augmenting Topologies., , , , and . IWANN (2), volume 11507 of Lecture Notes in Computer Science, page 678-686. Springer, (2019)Smart motion detection sensor based on video processing using self-organizing maps., , , and . Expert Syst. Appl., (2016)Layer multiplexing FPGA implementation for deep back-propagation learning., , , and . Integr. Comput. Aided Eng., 24 (2): 171-185 (2017)Exploratory Data Analysis and Foreground Detection with the Growing Hierarchical Neural Forest., , , and . Neural Process. Lett., 52 (3): 2537-2563 (2020)Thermal comfort estimation using a neurocomputational model., , , , and . LA-CCI, page 1-5. IEEE, (2016)Prediction of Learning Improvement in Mathematics through a Video Game using Neurocomputational Models., , , and . ICAART (2), page 554-559. SciTePress, (2019)Solving Scheduling Problems with Genetic Algorithms Using a Priority Encoding Scheme., , , , , , and . IWANN (1), volume 10305 of Lecture Notes in Computer Science, page 52-61. Springer, (2017)FPGA Implementation Comparison Between C-Mantec and Back-Propagation Neural Network Algorithms., , , and . IWANN (2), volume 9095 of Lecture Notes in Computer Science, page 197-208. Springer, (2015)Improving learning and generalization capabilities of the C-Mantec constructive neural network algorithm., , , , and . Neural Comput. Appl., 32 (13): 8955-8963 (2020)