Abstract: This study proposes a low-level radio frequency (LLRF) feedback control algorithm based on reinforcement learning (RL) using the soft actor–critic (SAC) and proximal policy optimization (PPO ...
The rapid adoption of electric vehicles (EVs) has introduced significant challenges in planning and optimizing charging infrastructure, especially along extensive road networks. This paper presents a ...
Abstract: With the increasing demand of high-precision data acquisition card in application, noise suppression in the process of signal acquisition becomes very important. The existence of noise will ...
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: In the field of remote sensing image processing, remote sensing image object detection is a crucial undertaking. However, the existing object detection algorithms have a considerable number ...
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 ...
A Dimensional Order Search Based Mapping Algorithm for Deploying DNNs onto Many-Core Neuromorphic IC
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: This paper investigates efficient algorithm for Markov Decision Processes (MDPs) through Linear programming (LP). Generally, solving large-scale MDPs via standard LP solvers faces ...
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