Dual-Control Bi-Space Surrogate-Assisted Evolutionary Algorithm
A framework that combines dual control mechanisms for candidate generation and infill criterion selection in surrogate-assisted evolutionary algorithms.
A framework that combines dual control mechanisms for candidate generation and infill criterion selection in surrogate-assisted evolutionary algorithms.
The additional resources and time required to manage and control a system, which can impact overall performance.
The process of using software tools to model and analyze the behavior of a system before physical implementation.
The ability to perform tasks using minimal energy, particularly important in the design of communication systems to reduce power consumption.
A family of loss functions that generalizes the notion of distance between points in a convex space.
The use of field-programmable gate arrays to implement and test hardware designs, allowing for reconfigurable hardware solutions.
A control mechanism that adapts to different operational scenarios to optimize resource utilization and minimize overhead in communication systems.
An integrated approach to designing hardware and software systems together to optimize performance and efficiency.
A communication architecture that allows for efficient data transfer in neuromorphic systems by dynamically managing segments of the bus based on activity levels.
Computing hardware designed to mimic the neural structure and functioning of the human brain, often used for energy-efficient processing of neural networks.