This course delves into the interdisciplinary field of neuromorphic engineering, which involves the design inspired by the structure, function, and dynamics of the human brain.

Main chapters:

Introduction to Neuromorphic Engineering:

Overview of neuromorphic systems

Comparison with traditional computing paradigms

Neuroanatomy and physiology

Synaptic dynamics and plasticity

Neuronal signaling and network models

Computational neuroscience principles

Analog vs. digital neuromorphic circuits

Spiking neural networks

Memristors and other novel devices

Hybrid modeling approaches

Neuromorphic Architectures

Energy-efficient designs

Scalability and integration challenges

Sensory processing (vision, audition)

By the end of the course, students will:

Understand the fundamental principles of neuromorphic engineering.

Be able to design and implement basic neuromorphic systems.

Explore the potential applications and limitations of neuromorphic technologies