Abstract: Aiming at the problem that mainlobe distortion and peak offset caused by mainlobe interference in wideband beamforming, a mainlobe maintenance (MM) wideband beamforming algorithm based on ...
Abstract: This letter proposes a hierarchical multistate optimization (HMO) method for the microstrip reconfigurable bandpass filter (RBPF). HMO algorithm nests the inner global optimization algorithm ...
Abstract: The main drawback of the second-order Volterra (SOV) filter is that its coefficients increase exponentially with the length of the memory, which has promoted the development of ...
Many-core neuromorphic integrated circuits (ICs) have the potential advantages of low power consumption, high parallelism, etc. for the edge computing of deep learning. A key problem in the ...
Abstract: This letter studies the issue of robust multitask distributed estimation under the error-in-variable (EIV) model where input noise and output impulsive noise are considered. In such cases, ...
Abstract: Autonomous vehicles require highly reliable collision-free capabilities, necessitating extensive research in path planning. Path planning determines an optimal path, crucial for safe and ...
Abstract: The integrated scheduling problem of cranes and automated guided vehicles (AGVs) in automated container terminals is a crucial area of concern for ports. In the terminal with AGV-supports in ...
Abstract: The main challenge faced by spaceborne SAR imaging in high squint case is the severe range-azimuth coupling caused by variation of azimuth frequency with slant range, which makes it ...
Abstract: This paper investigates efficient algorithm for Markov Decision Processes (MDPs) through Linear programming (LP). Generally, solving large-scale MDPs via standard LP solvers faces ...
Abstract: This paper investigates the optimization of the FedDyn algorithm in Federated Learning (FL). Federated Learning is a distributed machine learning framework that enables model training on ...
Abstract: This letter explores mobile molecular communication, where bio-nanomachines interact and coordinate movement using signal molecules in aqueous environments. In the system studied, a sender ...
Abstract: Deep Reinforcement Learning (DRL) enable several areas of artificial intelligence, including perception recognition, expert system, recommender program and game. Also, graph neural networks ...