Maisam Jalilian
Papers
1
Total Citations
7
H-Index
1
About
Maisam Jalilian is a researcher at the intersection of neuromorphic engineering and power electronics, whose work pioneers the use of biologically inspired spiking neural networks for practical signal generation. His most cited paper, "Pulse width modulation (PWM) signals using spiking neuronal networks" (2017, 7 citations), introduces a novel digital approach to constructing PWM signals by leveraging the Izhikevich neuron model on an FPGA platform. This innovative method translates neural dynamics into precise control signals for applications in robotics and power converters, bridging the gap between computational neuroscience and real-world electronic systems. Jalilian’s contributions demonstrate how spiking patterns can replace traditional PWM generation techniques, offering potential advantages in efficiency and adaptability. His work stands out for its interdisciplinary vision, merging the principles of neural computation with hardware implementation. While his citation count reflects an emerging career, the foundational nature of this research positions him as a promising figure in neuromorphic control systems, with implications for smarter, more energy-efficient electronics.
Research Focus
Key Achievements
Top Papers
- 1Pulse width modulation (PWM) signals using spiking neuronal networks7 citations · 2017