Neuromorphic Paradigm: Quasi-Digital and Neuromorphic Signals

This lecture introduces the concept of neuromorphic paradigm, focusing on the integration of quasi-digital and neuromorphic signals for efficient information transmission. The instructor discusses the use of spikes and frequency in signal encoding, emphasizing the energy-saving benefits of asynchronous event-driven systems. By combining the best aspects of both approaches, the lecture explores the application of these principles in biomedical engineering, particularly in tactile sensing systems. The discussion delves into the architectural design considerations for hierarchical sensor networks and the advantages of utilizing a hybrid approach. Through examples and explanations, the instructor illustrates how the human body's natural information exchange mechanisms can inspire innovative solutions in electronic systems.