English
Related papers

Related papers: A Fast, robust algorithm for power line interferen…

200 papers

We report on the realization of an optical phase noise cancellation technique by passively embedding the optical phase information into a radio frequency (RF) signal and shifting the optical frequency with the amount of phase noise…

Instrumentation and Detectors · Physics 2020-07-30 Liang Hu , Xueyang Tian , Guiling Wu , Jianping Chen

The multi-dithering method has been well verified in phase locking of polarization coherent combination experiment. However, it is hard to apply to low repetition frequency pulsed lasers, since there exists an overlap frequency domain…

Signal Processing · Electrical Eng. & Systems 2022-03-10 Jiali Zhang , Jie Cao , Qun Hao , Yang Cheng , Liquan Dong , Bin Han , Xuesheng Liu

Improving the interpretability of deep neural networks has recently gained increased attention, especially when the power of deep learning is leveraged to solve problems in physics. Interpretability helps us understand a model's ability to…

Sound · Computer Science 2023-10-12 Karim Helwani , Erfan Soltanmohammadi , Michael M. Goodwin

The significant imbalance between power generation and load caused by severe disturbance may make the power system unable to maintain a steady frequency. If the post-disturbance dynamic frequency features can be predicted and emergency…

Signal Processing · Electrical Eng. & Systems 2019-09-23 Jintian Lin , Yichao Zhang , Xiaoru Wang , Qingyue Chen

Recent advances in associative memory design through structured pattern sets and graph-based inference algorithms have allowed reliable learning and recall of an exponential number of patterns. Although these designs correct external errors…

Neural and Evolutionary Computing · Computer Science 2014-03-14 Amin Karbasi , Amir Hesam Salavati , Amin Shokrollahi , Lav R. Varshney

Spiking neural networks (SNNs) have garnered interest due to their energy efficiency and superior effectiveness on neuromorphic chips compared with traditional artificial neural networks (ANNs). One of the mainstream approaches to…

Neural and Evolutionary Computing · Computer Science 2024-04-29 Zhipeng Huang , Jianhao Ding , Zhiyu Pan , Haoran Li , Ying Fang , Zhaofei Yu , Jian K. Liu

We present a technique that we call coherent line removal, for removing external coherent interference from gravitational wave interferometer data. We illustrate the usefulness of this technique applying it to the the data produced by the…

General Relativity and Quantum Cosmology · Physics 2007-05-23 A. M. Sintes , B. F. Schutz

We explore the robustness of recurrent neural networks when the computations within the network are noisy. One of the motivations for looking into this problem is to reduce the high power cost of conventional computing of neural network…

Machine Learning · Computer Science 2018-07-18 Minghai Qin , Dejan Vucinic

This work introduces an economic solution for the problems of sound insulation of recording studios. Sound insulation at wall resonance frequency is weak. Instead of acoustical treatment, a digital filter is used to eliminate the effects of…

Sound · Computer Science 2010-06-07 Mahmoud I. A. Abdalla

Acoustic Echo Cancellation (AEC) plays a key role in voice interaction. Due to the explicit mathematical principle and intelligent nature to accommodate conditions, adaptive filters with different types of implementations are always used…

Sound · Computer Science 2020-05-20 Lu Ma , Hua Huang , Pei Zhao , Tengrong Su

This paper introduces a low-complexity memoryless linearizer for suppression of distortion in analog-to-digital interfaces. It is inspired by neural networks, but has a substantially lower complexity than the neural-network schemes that…

Signal Processing · Electrical Eng. & Systems 2025-09-19 Deijany Rodriguez Linares , Håkan Johansson

This paper introduces low-complexity frequency-dependent (memory) linearizers designed to suppress nonlinear distortion in analog-to-digital interfaces. Two different linearizers are considered, based on nonlinearity models which correspond…

Signal Processing · Electrical Eng. & Systems 2025-12-24 Deijany Rodriguez Linares , Håkan Johansson

We propose a general framework for reconstructing and denoising single entries of incomplete and noisy entries. We describe: effective algorithms for deciding if and entry can be reconstructed and, if so, for reconstructing and denoising…

Machine Learning · Statistics 2013-04-02 Franz J. Király , Louis Theran

We study two aspects of noisy computations during inference. The first aspect is how to mitigate their side effects for naturally trained deep learning systems. One of the motivations for looking into this problem is to reduce the high…

Machine Learning · Computer Science 2018-11-28 Minghai Qin , Dejan Vucinic

This paper introduces an innovative method for reducing the computational complexity of deep neural networks in real-time speech enhancement on resource-constrained devices. The proposed approach utilizes a two-stage processing framework,…

Audio and Speech Processing · Electrical Eng. & Systems 2024-06-10 Shrishti Saha Shetu , Soumitro Chakrabarty , Oliver Thiergart , Edwin Mabande

Nonlinear signal distortions are one of the primary factors limiting the capacity and reach of optical transmission systems. Currently, several approaches exist for compensating nonlinear distortions, but for practical implementation,…

Optics · Physics 2024-10-01 Alexey Redyuk , Evgeny Shevelev , Vitaly Danilko , Mikhail Fedoruk

We introduce a new supervised learning algorithm based to train spiking neural networks for classification. The algorithm overcomes a limitation of existing multi-spike learning methods: it solves the problem of interference between…

Neural and Evolutionary Computing · Computer Science 2021-08-12 Huy Le Nguyen , Dominique Chu

The stability of AC power grids relies on ancillary services that mitigate frequency fluctuations. The electromechanical inertia of large synchronous generators is currently the only resource to absorb frequency disturbances on sub-second…

Systems and Control · Electrical Eng. & Systems 2025-05-21 Julian Fritzsch , Philippe Jacquod

Noise is a part of data whether the data is from measurement, experiment or ... A few techniques are suggested for noise reduction to improve the data quality in recent years some of which are based on wavelet, orthogonalization and neural…

Computational Engineering, Finance, and Science · Computer Science 2023-08-02 Negin Bagherpour , Abbas Mohammadiyan

The present paper develops recursive algorithms to track shifts in the resonance frequency of linear systems in real time. To date, automatic resonance tracking has been limited to non-model-based approaches, which rely solely on the phase…

Optimization and Control · Mathematics 2020-12-22 Thomas Vasileiou