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A Combined Step-size Filtered-x Affine Projection Champernowne Algorithm for Active Noise Control
2024 24th International Conference on Control, Automation and Systems (ICCAS)
Year: 2024 | Conference Paper |
The study proposes the combined step-size affine projection Champernowne adaptive filter (CSS-APCMAF), addressing the back-and-forth relationship between convergence rate and steady-state misalignment in fixed step-size adaptive filtering algorithms. Additionally, the study introduces a new approach to active noise control using the combined step-size filtered-x affine projection Champernowne adap...Show More
A Bias-Compensated Robust Affine Projection Algorithm Using Variable Matrix-type Step Size
2024 32nd European Signal Processing Conference (EUSIPCO)
Year: 2024 | Conference Paper |
We propose a novel system identification algorithm using adpative filter, which demonstrates superior performance compared to existing robust Affine Projection Algorithms (APAs). Through systematic simulations, we validate the effectiveness of our algorithm in handling impulsive noise and input noise, crucial issues in practical applications of adaptive filters. Our approach incorporates variable ...Show More
Combined step-size generalized continuous mixed p-norm algorithm
2023 Third International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)
Year: 2023 | Conference Paper |
This paper proposes a robust combined step-size generalized variable step-size continuous mixed p-norm (CSS-GVSS-CMPN) algorithm to improve performance in an environment with impulsive noise. GVSS-CMPN algorithm is derived from a CMPN cost function and has outstanding performance. The proposed algorithm introduces a combined step-size (CSS) strategy to resolve the trade-off problem that occurs in ...Show More
Frequency-Domain Data Augmentation of Vibration Data for Fault Diagnosis using Deep Neural Networks
Minseon Gwak;Seunghyun Ryu;Yongbeom Park;Hyeon-Woo Na;PooGyeon Park
2022 22nd International Conference on Control, Automation and Systems (ICCAS)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
This paper proposes a data augmentation method for vibration data-based fault diagnosis using deep neural networks. The proposed method is devised to deal with the practical problem in applying trained models to facilities, where frequency-domain features of data vary according to the change in the working environment of the facilities. In the proposed method, training data are augmented by scalin...Show More
Cleaning Up Mislabeled Data via Image Plotting Method and Self-Attention Module
2022 22nd International Conference on Control, Automation and Systems (ICCAS)
Year: 2022 | Conference Paper |
This paper proposes the method for cleaning up label noise in multivariate time-series outlier data. An image plotting method is proposed to reflect the tendency of original time-series data. The image data generated from the plotting method shows effectiveness, since the data can be smoothly utilized in label noise cleaning process and easy to analyze. To verify the availability of plotted data, ...Show More
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