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Active road noise control (ARNC) is an effective method for mitigating low-frequency noise in vehicle cabins. Previous work introduced a decoupling-whitening frequency domain filtered-error least mean square (DWFDFeLMS) algorithm, which exhibits rapid convergence characteristics for steady-state environments. However, uncorrelated disturbances significantly impact the convergence performance and stability of adaptive algorithms in practical applications. In this paper, a coherence-based robust frequency-dependent variable step size method is proposed to dynamically adjust the step size, using the multichannel coherence coefficients between reference signals and error signals for system stability. Additionally, it is combined with the DWFDFeLMS algorithm for fast convergence speed in ARNC systems. The proposed algorithm ensures fast initial convergence, small steady-state error, and resilience to in-cabin interference. The superiority of this algorithm in terms of convergence speed and stability is confirmed through simulations with measured road noise data and in a real-time ANC system in a car cabin.
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http://dx.doi.org/10.1121/10.0038751 | DOI Listing |
Environ Pollut
September 2025
Centre for Environmental and Marine Studies (CESAM) & Department of Biology, University of Aveiro, Portugal. Electronic address:
Printed circuit boards (PCB) present a complex recycling challenge due to their miniaturisation and different constituents (e.g., metals, plastics), highlighting the need for integrated bioprocessing approaches.
View Article and Find Full Text PDFBiomed Phys Eng Express
September 2025
electrical engineering department, Indian Institute of Technology Roorkee, Research wing, electrical department, Roorkee, uttrakhand, 247664, INDIA.
Imagined speech classification involves decoding brain signals to recognize verbalized thoughts or intentions without actual speech production. This technology has significant implications for individuals with speech impairments, offering a means to communicate through neural signals. The prime objective of this work is to propose an innovative machine learning (ML) based classification methodology that combines electroencephalogram (EEG) data augmentation using a sliding window technique with statistical feature extraction from the amplitude and phase spectrum of frequency domain EEG segments.
View Article and Find Full Text PDFLangmuir
September 2025
Product & Process Engineering, Department of Chemical Engineering, Faculty of Applied Sciences, Delft University of Technology, 2629 HZ Delft, The Netherlands.
Noble metal nanoparticles (NPs), particularly platinum (Pt), are widely used in heterogeneous catalysis due to their exceptional activity. However, controlling their size and preventing sintering during synthesis remains a major challenge, especially when aiming for high dispersion and stability on supports such as graphene. Atomic layer deposition (ALD) has emerged as a promising method to address these issues, yet conventional processes often lead to broad particle size distributions (PSDs).
View Article and Find Full Text PDFPolicy optimization methods are promising to tackle high-complexity reinforcement learning (RL) tasks with multiple agents. In this article, we derive a general trust region for policy optimization methods by considering the effect of subpolicy combinations among agents in multiagent environments. Based on this trust region, we propose an inductive objective to train the policy function, which can ensure agents learn monotonically improving policies.
View Article and Find Full Text PDFJ Adv Nurs
September 2025
Nursing Department, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Aim: To systematically analyse international empirical literature and establish a comprehensive understanding of the push and pull factors influencing retention and turnover among mid-career nurses.
Design: An integrative review.
Data Sources: PubMed, Web of Science, Scopus, EMBASE (Ovid), and CINAHL (EBSCO) were searched for studies published between January 2001 and November 2024.