Cognition-Driven Modeling and Optimization Technology for Multi-Disciplinary Design of High-Frequency Components and Communication Subsystems

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Our proposed research will be dedicated to the scale and critical mass necessary for the emerging technology of cognition-driven modeling and design of RF/microwave and terahertz components and multi-giga-bit communication circuits. Built-on our highly recognized work on neural network and space mapping modeling and optimization, the proposed cognition-driven approach will elevate the state-of-the-art of high-frequency electronic modeling and design into a new level by formally involving aspects of thinking (human intuition, decision-making etc.), with new opportunities to increase the effectiveness of automated modeling and design, to better harness expertise and knowledge such as empirical models, equivalent circuits, semi-analytical equations, internal electromagnetic structural information, together with multiphysics design and simulation. New techniques formalizing the cognition-driven algorithms with detailed electromagnetic and multiphysics simulations will be developed to achieve fast and accurate modeling and optimization solutions. The technology will be further generalized to address multi-disciplinary modeling and design needs, such as, electrical/electromagnetic/ thermal/stress/EMC design. Our goal is to create a new critical mass for developing a comprehensive technology to serve as the engine for modeling and design optimization of next generation of high-frequency electronic devices, components and subsystems to help dramatically increase the productivity of wireless and wireline communications and information processing systems design.