Maximum Correntropy Quaternion Kalman Filter
To solve the estimation problem in three-dimensional space, the quaternion Kalman filter (QKF) is developed for quaternion-valued signals using the well-known minimum mean square error (MMSE) criterion under the Gaussian assumption. However, when the system is disturbed by some non-Gaussian impulsive noises, the performance of QKF will be degraded significantly. To address this issue, this paper first develops a new QKF, called the maximum correntropy quaternion Kalman filter (MCQKF) by using the robust maximum correntropy criterion (MCC) instead of the MMSE criterion to improve the robustness of QKF against non-Gaussian i...
Source: IEEE Transactions on Signal Processing - August 17, 2023 Category: Biomedical Engineering Source Type: research

Inverse Extended Kalman Filter—Part I: Fundamentals
Recent advances in counter-adversarial systems have garnered significant research attention to inverse filtering from a Bayesian perspective. For example, interest in estimating the adversary’s Kalman filter tracked estimate with the purpose of predicting the adversary’s future steps has led to recent formulations of inverse Kalman filter (I-KF). In this context of inverse filtering, we address the key challenges of non-linear process dynamics and unknown input to the forward filter by proposing an inverse extended Kalman filter (I-EKF). The purpose of this paper and the companion paper (Part II) is to develop the theo...
Source: IEEE Transactions on Signal Processing - August 17, 2023 Category: Biomedical Engineering Source Type: research

Convolutional Filters and Neural Networks With Noncommutative Algebras
In this paper we introduce and study the algebraic generalization of non commutative convolutional neural networks. We leverage the theory of algebraic signal processing to model convolutional non commutative architectures, and we derive concrete stability bounds that extend those obtained in the literature for commutative convolutional neural networks. We show that non commutative convolutional architectures can be stable to deformations on the space of operators. We develop the spectral representation of non commutative signal models to show that non commutative filters process Fourier components independently of each ot...
Source: IEEE Transactions on Signal Processing - August 16, 2023 Category: Biomedical Engineering Source Type: research

Nonlinear Graph Wavelets via Medianfication
Graph wavelet transforms allow for the effective representation of signals that are defined over irregular domains. The transform coefficients should be sparse, and encode salient features of a signal. In many situations, these salient features appear as discontinuities in the signal, e.g. physical edges in natural images. The transforms facilitate the development of various graph signal processing tasks, e.g. feature extraction or compression. The graph wavelets proposed in the literature are linear transforms, and employ linear filters that consist essentially of mean operations. We propose the construction of nonlinear ...
Source: IEEE Transactions on Signal Processing - August 15, 2023 Category: Biomedical Engineering Source Type: research

Low-Complexity Channel Estimation for Massive MIMO Systems With Decentralized Baseband Processing
The traditional centralized baseband processing architecture is faced with the bottlenecks of high computation complexity and excessive fronthaul communication, especially when the number of antennas at the base station (BS) is large. To cope with these two challenges, the decentralized baseband processing (DBP) architecture has been proposed, where the BS antennas are partitioned into multiple clusters and each is connected to a local baseband unit (BBU). In this paper, we are interested in the low-complexity distributed channel estimation (CE) method under such DBP architecture, which is rarely studied in the literature....
Source: IEEE Transactions on Signal Processing - August 15, 2023 Category: Biomedical Engineering Source Type: research

A Fast Successive QP Algorithm for General Mean-Variance Portfolio Optimization
The mean and variance of portfolio returns are the standard quantities to measure the expected return and risk of a portfolio. Efficient portfolios that provide optimal trade-offs between mean and variance warrant consideration. To express a preference among these efficient portfolios, investors have put forward many mean-variance portfolio (MVP) formulations which date back to the classical Markowitz portfolio. However, most existing algorithms are highly specialized to particular formulations and cannot be generalized for broader applications. Therefore, a fast and unified algorithm would be extremely beneficial. In this...
Source: IEEE Transactions on Signal Processing - August 15, 2023 Category: Biomedical Engineering Source Type: research

Uplink Sensing Using CSI Ratio in Perceptive Mobile Networks
Uplink sensing in perceptive mobile networks (PMNs), which uses uplink communication signals for sensing the environment around a base station, faces challenging issues of clock asynchronism and the requirement of a line-of-sight (LOS) path between transmitters and receivers. The channel state information (CSI) ratio has been applied to resolve these issues, however, current research on the CSI ratio is limited to Doppler estimation in a single dynamic path. This paper proposes an advanced parameter estimation scheme that can extract multiple dynamic parameters, including Doppler frequency, angle-of-arrival (AoA), and dela...
Source: IEEE Transactions on Signal Processing - August 15, 2023 Category: Biomedical Engineering Source Type: research

Compressed Sensing Radar Detectors Under the Row-Orthogonal Design Model: A Statistical Mechanics Perspective
Compressed sensing (CS) model of complex-valued data can represent the signal recovery process of many types of radar systems, especially when the measurement matrix is row-orthogonal. Based on debiased least absolute shrinkage and selection operator (LASSO), the detection problem under the Gaussian random design model, i.e. the elements of the measurement matrix are drawn from a Gaussian distribution, is studied by literature. However, these approaches are unsuitable for the row-orthogonal measurement matrices, which are of more practical relevance. In view of statistical mechanics approaches, we provide derivations of mo...
Source: IEEE Transactions on Signal Processing - August 15, 2023 Category: Biomedical Engineering Source Type: research

Asymptotic Analysis of Federated Learning Under Event-Triggered Communication
Federated learning (FL) is a collaborative machine learning (ML) paradigm based on persistent communication between a central server and multiple edge devices. However, frequent communication of large ML models can incur considerable communication resources, especially costly for wireless network nodes. In this paper, we develop a communication-efficient protocol to reduce the number of communication instances in each round while maintaining convergence rate and asymptotic distribution properties. First, we propose a novel communication-efficient FL algorithm that utilizes an event-triggered communication mechanism, where ...
Source: IEEE Transactions on Signal Processing - August 15, 2023 Category: Biomedical Engineering Source Type: research

Variable-Wise Diagonal Preconditioning for Primal-Dual Splitting: Design and Applications
This paper proposes a method for designing diagonal preconditioners for a preconditioned primal-dual splitting method (P-PDS), an efficient algorithm that solves nonsmooth convex optimization problems. To speed up the convergence of P-PDS, a design method has been proposed to automatically determine appropriate preconditioners from the problem structure. However, the existing method has two limitations. One is that it directly accesses all elements of matrices representing linear operators involved in a given problem, which is inconvenient for handling linear operators implemented as procedures rather than matrices. The ot...
Source: IEEE Transactions on Signal Processing - August 14, 2023 Category: Biomedical Engineering Source Type: research

Waveform Design for Wireless Power Transfer With Power Amplifier and Energy Harvester Non-Linearities
Waveform optimization has shown its great potential to boost the performance of far-field wireless power transfer (WPT). Current research has optimized transmit waveform, adaptive to channel state information, to maximize the harvested power in WPT while accounting for the energy harvester (EH)’s non-linearity. However, the existing transmit waveform design disregards the non-linear high power amplifiers (HPA) at the transmitter. Driven by this, this article optimizes a multi-carrier waveform at the input of HPA to maximize the harvested DC power considering both HPA's and EH's non-linearities. Two opt...
Source: IEEE Transactions on Signal Processing - August 8, 2023 Category: Biomedical Engineering Source Type: research

Robust Graph Filter Identification and Graph Denoising From Signal Observations
When facing graph signal processing tasks, it is typically assumed that the graph describing the support of the signals is known. However, in many relevant applications the available graph suffers from observational errors and perturbations. As a result, any method that relies on the graph topology and ignores the presence of perturbations may yield suboptimal results. Motivated by this, we propose a novel approach for handling perturbations on the links of the graph and apply it to the problem of robust graph filter (GF) identification from input-output observations. Different from existing works, we formulate a non-conve...
Source: IEEE Transactions on Signal Processing - August 7, 2023 Category: Biomedical Engineering Source Type: research

Upper Bound of Null Space Constant $\rho(p,t,A,k)$ and High-Order Restricted Isometry Constant $\delta_{tk}$ for Sparse Recovery via $\ell_{p}$ Minimization
The $\boldsymbol{\ell_{p}}$ null space property ($\boldsymbol{\ell_{p}}$-NSP) and restricted isometry property (RIP) are two important frames for sparse signal recovery. New sufficient conditions in terms of $\boldsymbol{\ell_{p}}$-NSP and RIP are respectively developed in this paper. Firstly, we characterize the $\boldsymbol{\ell_{p}}$ robust null space property ($\boldsymbol{\ell_{p}}$-RNSP) concerning two high-order restricted isometry constants. Then we derive an upper bound of $\boldsymbol{\ell_{p}}$-NSC $\boldsymbol{\rho(p,t,A,k)}$ for the exact recovery of $\boldsymbol{k}$-sparse signals via $\boldsymbol{\ell_{p}}$ ...
Source: IEEE Transactions on Signal Processing - August 7, 2023 Category: Biomedical Engineering Source Type: research

FedUR: Federated Learning Optimization Through Adaptive Centralized Learning Optimizers
Introducing adaptiveness to federated learning has recently ushered in a new way to optimize its convergence performance. However, adaptive learning strategies originally designed in centralized machine learning are in naїve extended to federated learning in existing works, which does not necessarily improve convergence performance and further reduce communication overhead as expected. In this paper, we fully investigate those centralized learning-based adaptive learning strategies, and propose an adaptive Federated learning algorithm targeting the model parameter Update Rule, called FedUR. Convergence upper bounds ...
Source: IEEE Transactions on Signal Processing - August 4, 2023 Category: Biomedical Engineering Source Type: research

Overcomplete Multiscale Dictionary of Slepian Functions for HEALPix on the Sphere
We present a framework for exact analytical computation of bandlimited Slepian functions for Hierarchical Equal Area iso-Latitude Pixelization (HEALPix) scheme on the sphere. Slepian functions are bandlimited eigenfunctions obtained by solving the spatial-spectral concentration problem on the sphere. Utilizing rotational symmetries between the HEALPix pixels, we employ Wigner-$D$ functions to efficiently compute the bandlimited Slepian functions at different resolutions of the HEALPix partitioning scheme. We present convergence criteria for the infinite series expansions involved in the analytical expressions, analyze the ...
Source: IEEE Transactions on Signal Processing - July 25, 2023 Category: Biomedical Engineering Source Type: research