Design and Energy Evaluation of Neural Network Implementations on FPGA

This traineeship focuses on the design and energy evaluation of neural network implementations onFPGA platforms. The work includes developing and optimizing neural network models for reconfigurable hardware, with attention to performance, latency, power consumption, and resource utilization. FPGA programming will be carried out using MATLAB and Simulink through a model-based design approach. Neural networks will be designed and simulated in MATLAB/Simulink. Experimental measurements will be performed to assess computational efficiency and energy consumption. The objective is to identify efficient, low-power FPGA-based implementations of artificial intelligence algorithms for embedded and real-time applications.