Neural Processing Letters https://doi.org/10.1007/s11063-022-10814-9 A Parallel Reconfigurable Architecture for Scalable LVQ Neural Networks Marwa Gam 1,2 · Mohamed Boubaker 1 · Khaled Ben Khalifa 1,3 · Mohamed Hedi Bedoui 1 Accepted: 4 April 2022 © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract In this work, a new architecture for implementing LVQ neural networks is presented. The pro- posed solution exploits the advantages of local parallelization in elementary neuro-processors and partial dynamic reconfiguration to define the number of elementary processors used according to context and requirements. The RP-LVQ architecture is generic, scalable and partially and dynamically reconfigurable to ensure the adaptability of the LVQ network to the application context while respecting the constraints by matching parallelism with the architectures. As a validation of the RP-LVQ, we report the speed and power performance of several LVQ network architectures’ implementation on a Xilinx zynq-7000 FPGA. For a 1,024 neuron-topology in the hidden layer and a parallelism rate of β = 5, we achieved 10,070 million connections per second at a 100 MHz clock frequency with a 16.58 mw power consumption. These promising results open up ways for the implementation of applications where the flexibility and adaptability to the context or user are needed. Keywords ANN · RP-LVQ · Scalable topology · Parallel architecture · Partial dynamic reconfiguration · Adaptability 1 Introduction Artificial Neural Networks (ANNs) are processing models that are inspired from the structure and physiology of the human brain, aiming at mimicking its natural learning abilities. They are typically made of computing units that are non-linear, parallel, distributed and simply layer- interconnected. Parallelism, modularity and dynamic adaptation are generally associated with B Mohamed Boubaker boubaker.mohamed@gmail.com 1 Technology and Medical Imaging Laboratory, Faculty of Medicine Monastir, University of Monastir, 5019 Monastir, Tunisia 2 National Engineering School of Sousse, University of Sousse, Erriyadh, BP 264, 4023 Sousse, Tunisia 3 Institut Supérieur des Sciences Appliquées et de Technologie de Sousse, Université de Sousse, 4003 Sousse, Tunisia 123