Stochastic Neuromorphic Cyber Physical Systems Design

Abstract

In a time marked by rapid technological advancements, the merging of digital and physical realms has given rise to a paradigm that goes beyond traditional limits – known as the Cyber-Physical System (CPS). Characterized by the complex interaction between artificial intelligence and tangible world, CPS has become a crucial element of modern society, influencing various sectors such as manufacturing, healthcare, transportation, and energy. Amidst this evolving scenario, the integration of neuromorphic concepts brings a cutting-edge aspect, highlighting the combination of biological insights with probabilistic computational approaches. The pursuit of enhanced, flexible, and intelligent systems has spurred the investigation into innovative computational frameworks. Neuromorphic engineering, drawing inspiration from the remarkable efficiency of the human brain, presents a groundbreaking approach to replicating cognitive functions and sensory capabilities in artificial systems. Concurrently, stochastic processes and probabilistic techniques have become essential instruments for capturing and simulating the inherent uncertainties prevalent in real-world settings. The convergence of neuromorphic and stochastic domains gives rise to the concept of "Stochastic Neuromorphic Cyber Physical Design," enabling computational systems not only to perceive, analyze, and interact with the physical environment but also to do so with a foundation in stochastic cognition. In a period marked by the complex relationship between computing and physical aspects, Cyber-Physical Systems (CPS) has become a crucial field, encompassing various uses ranging from self-driving cars to intelligent production. There could be the possible collaboration between random processes, which address natural unpredictability, and neuromorphic technology, which replicates the effectiveness of biological thinking. The integration of neuromorphic computing with cyber-physical systems (CPS) has garnered significant attention as a promising avenue for realizing efficient, adaptable, and intelligent systems.