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Full Description
This book brings together a collection of rigorously peer-reviewed chapters that present recent theoretical, methodological, and applied developments in circuits, systems, and related interdisciplinary fields. This book reflects current research trends that combine classical system theory with emerging computational and data-driven approaches.
This book addresses key topics in modern engineering, including stochastic modeling and estimation, passivity analysis of multivariable systems, advanced optimization methods, and power and energy system analysis. Several chapters focus on practical challenges such as voltage stabilization following fault conditions, stochastic power flow in distribution networks, and monitoring of complex industrial processes using deep-learning techniques.
The growing impact of artificial intelligence on circuits and systems is highlighted through studies on ensemble learning for cybersecurity in IoT environments, reinforcement learning for adaptive control and dispatch, and automated analysis of AI-generated code. Additional chapters extend system-theoretic and optimization frameworks to applications in public health, workforce planning, organizational dynamics, and social choice modeling.
This book is intended for researchers, graduate students, and practitioners in electrical and computer engineering, control systems, and applied mathematics who seek an authoritative overview of current advances and emerging directions in circuits and systems research.
