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Nonlinear models are known to provide excellent performance in real-world applications that often operate in non-ideal conditions. However, such applications often require online processing to be performed with limited computational…

Machine Learning · Computer Science 2024-10-28 Danilo Comminiello , Alireza Nezamdoust , Simone Scardapane , Michele Scarpiniti , Amir Hussain , Aurelio Uncini

In this paper, we propose low-complexity local detectors and log-likelihood ratio (LLR) refinement techniques for a coded cell-free massive multiple input multiple output (CF- mMIMO) systems, where an iterative detection and decoding (IDD)…

Information Theory · Computer Science 2024-05-24 T. Ssettumba , Z. Shao , L. Landau , R. C. de Lamare

This paper proposes the \emph{multiresolution mode decomposition} as a novel model for adaptive time series analysis. The main conceptual innovation is the introduction of the \emph{multiresolution intrinsic mode function} (MIMF) of the…

Numerical Analysis · Mathematics 2019-08-30 Haizhao Yang

In this dissertation, we investigate the issue of robust localization in swarms of heterogeneous mobile agents with multiple and time-varying sensing modalities. Our focus is the development of filter-based and decoupled estimators under…

Robotics · Computer Science 2024-08-23 Roland Jung

In this work, we implement a relatively new analytical technique, the Improved Amplitude-Frequency Formulation (IAFF) method, approach for solving accurate approximate analytical solutions for strong nonlinear oscillators, which may contain…

Dynamical Systems · Mathematics 2021-10-05 R. Azami , D. D. Ganji , A. G. Davodi , H. Babazadeh

Turbulent space and astrophysical plasmas exhibit a complex dynamics, which involves nonlinear coupling across different temporal and spatial scales. There is growing evidence that impulsive events, such as magnetic reconnection…

Starting from a recent a posteriori error estimator for the finite element solution of the wave equation with explicit time-stepping [Grote, Lakkis, Santos, 2024], we devise a space-time adaptive strategy which includes both time evolving…

Numerical Analysis · Mathematics 2026-01-07 Marcus J. Grote , Omar Lakkis , Carina S. Santos

This paper revisits the design and optimization of parallel fast finite impulse response (FIR) filters using polyphase decomposition and iterated fast FIR algorithms (FFAs). Parallel FIR filtering enhances computational efficiency and…

Signal Processing · Electrical Eng. & Systems 2026-01-23 Keshab K. Parhi

The distributed adaptive signal fusion (DASF) framework allows to solve spatial filtering optimization problems in a distributed and adaptive fashion over a bandwidth-constrained wireless sensor network. The DASF algorithm requires each…

Signal Processing · Electrical Eng. & Systems 2025-05-02 Cem Ates Musluoglu , Alexander Bertrand

We propose an adaptive iteratively linearized finite element method (AILFEM) in the context of strongly monotone nonlinear operators in Hilbert spaces. The approach combines adaptive mesh-refinement with an energy-contractive linearization…

Numerical Analysis · Mathematics 2025-03-18 Ani Miraçi , Dirk Praetorius , Julian Streitberger

We propose a new solution to the blind source separation problem that factors mixed time-series signals into a sum of spatiotemporal modes, with the constraint that the temporal components are intrinsic mode functions (IMF's). The key…

Numerical Analysis · Mathematics 2018-06-25 Seth M. Hirsh , Bingni W. Brunton , J. Nathan Kutz

Matched filters are widely used to localise signal patterns due to their high efficiency and interpretability. However, their effectiveness deteriorates for low signal-to-noise ratio (SNR) signals, such as those recorded on edge devices,…

Signal Processing · Electrical Eng. & Systems 2025-09-01 Haozhe Tian , Qiyu Rao , Nina Moutonnet , Pietro Ferraro , Danilo Mandic

Since many decades, there is a general perception in literature that the Fourier methods are not suitable for the analysis of nonlinear and nonstationary data. In this paper, we propose a Fourier Decomposition Method (FDM) and demonstrate…

Methodology · Statistics 2017-03-16 Pushpendra Singh , Shiv Dutt Joshi , Rakesh Kumar Patney , Kaushik Saha

In this study, the Multivariate Empirical Mode Decomposition (MEMD) approach is applied to extract features from multi-channel EEG signals for mental state classification. MEMD is a data-adaptive analysis approach which is suitable…

Signal Processing · Electrical Eng. & Systems 2022-06-03 Monira Islam , Tan Lee

Modern time series are usually composed of multiple oscillatory components, with time-varying frequency and amplitude contaminated by noise. The signal processing mission is further challenged if each component has an oscillatory pattern,…

Signal Processing · Electrical Eng. & Systems 2021-10-04 Marcelo A. Colominas , Hau-Tieng Wu

This paper addresses the problem of estimating the modes of an observed non-stationary mixture signal in the presence of an arbitrary distributed noise. A novel Bayesian model is introduced to estimate the model parameters from the…

Signal Processing · Electrical Eng. & Systems 2022-03-31 Quentin Legros , Dominique Fourer , Sylvain Meignen , Marcelo A. Colominas

A digital finite impulse response (FIR) filter design is fully synthesizable, thanks to the mature CAD support of digital circuitry. On the contrary, analog mixed-signal (AMS) filter design is mostly a manual process, including architecture…

Systems and Control · Electrical Eng. & Systems 2021-12-16 Shiyu Su , Qiaochu Zhang , Juzheng Liu , Mohsen Hassanpourghadi , Rezwan Rasul , Mike Shuo-Wei Chen

This paper investigates the sensing potential of affine frequency division multiplexing (AFDM) in high-mobility integrated sensing and communication (ISAC) from the perspective of radar waveforms. We introduce an innovative parameter…

Signal Processing · Electrical Eng. & Systems 2026-04-14 Jiajun Zhu , Yanqun Tang , Cong Yi , Haoran Yin , Yuanhan Ni , Fan Liu , Zhiqiang Wei , Huseyin Arslan

The time-domain technique for impedance spectroscopy consists of computing the excitation voltage and current response Fourier images by fast or discrete Fourier transformation and calculating their relation. Here we propose an alternative…

Data Analysis, Statistics and Probability · Physics 2017-12-14 Daniil D. Stupin , Sergei V. Koniakhin , Nikolay A. Verlov , Michael V. Dubina

Iterative Proportional Fitting (IPF), combined with EM, is commonly used as an algorithm for likelihood maximization in undirected graphical models. In this paper, we present two iterative algorithms that generalize upon IPF. The first one…

Machine Learning · Computer Science 2013-01-07 Wim Wiegerinck , Tom Heskes