IEEE Transactions on Signal Processing This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Anisotropic Spherical Scattering Networks via Directional Spin Wavelet
Scattering networks on Euclidean domains are capable of analytically realizing signal representation invariant to transformations such as translation, rotation and scaling with wavelets. However, existing scattering networks defined on the sphere and Riemannian manifolds only consider axisymmetric wavelets and are restricted in representation by the isotropic filter structures. In this paper, we propose a novel anisotropic spherical scattering network to achieve multi-scale directional representation for spherical signals. The scattering transform is realized by cascading directional spin wavelets and modulus operators to ...
Source: IEEE Transactions on Signal Processing - September 6, 2023 Category: Biomedical Engineering Source Type: research

Distribution-Agnostic Linear Unbiased Estimation With Saturated Weights for Heterogeneous Data
The challenging problem of distribution-agnostic linear (weighted) unbiased estimation of a global parameter from heterogeneous and unbalanced data is addressed. This setup may originate in different signal processing contexts involving the joint processing of non-homogeneous groups of data whose statistical distribution is unknown, with (possibly highly) diverse sample sizes. Since sample estimators of the local variances are inaccurate in the low-sample regime, suitable weighting schemes are required. For this problem, we study a family of estimators based on the idea of trimmed weights, i.e., proportional to the sample ...
Source: IEEE Transactions on Signal Processing - September 6, 2023 Category: Biomedical Engineering Source Type: research

On the Decentralized Stochastic Gradient Descent With Markov Chain Sampling
The decentralized stochastic gradient method emerges as a promising solution for solving large-scale machine learning problems. This paper studies the decentralized Markov chain gradient descent (DMGD), a variant of the decentralized stochastic gradient method, which draws random samples along the trajectory of a Markov chain. DMGD arises when obtaining independent samples is costly or impossible, excluding the use of the traditional stochastic gradient algorithms. Specifically, we consider the DMGD over a connected graph, where each node only communicates with its neighbors by sending and receiving the intermediate result...
Source: IEEE Transactions on Signal Processing - September 6, 2023 Category: Biomedical Engineering Source Type: research

Data Fusion for Multipath-Based SLAM: Combining Information From Multiple Propagation Paths
Multipath-based simultaneous localization and mapping (SLAM) is an emerging paradigm for accurate indoor localization constrained by limited navigation resources. The goal of multipath-based SLAM is to support the estimation of time-varying positions of mobile agents by detecting and localizing radio-reflective surfaces in the environment. In existing Bayesian methods, a propagation surface is represented by the mirror image of each physical anchor (PA) across that surface – known as the corresponding “virtual anchor” (VA). Due to this VAs representation, each propagation path is mapped individually. Existing methods...
Source: IEEE Transactions on Signal Processing - September 6, 2023 Category: Biomedical Engineering Source Type: research

A New Ridge Detector Localizing Strong Interference in Multicomponent Signals in the Time-Frequency Plane
In this article, we define a new ridge detector that enables to localize strong interference in multicomponent signals in the time-frequency (TF) plane. Each mode of a multicomponent signal can usually be associated with a ridge in the TF plane, but this is no longer the case when strong interferences occur in the signal. The new ridge detector we propose is thus designed to determine when such situations happen in the TF plane. We show that this knowledge helps to determine an appropriate window length in the definition of the spectrogram, as well as the nature of the strong interference detected. An application of the pr...
Source: IEEE Transactions on Signal Processing - September 6, 2023 Category: Biomedical Engineering Source Type: research

A Graphical Model for Fusing Diverse Microbiome Data
We present a computationally scalable variational Expectation-Maximization (EM) algorithm for inferring the latent variables and the parameters of the model. The inferred latent variables provide a common dimensionality reduction for visualizing the data and the inferred parameters provide a predictive posterior distribution. In addition to simulation studies that demonstrate the variational EM procedure, we apply our model to a bacterial microbiome dataset. (Source: IEEE Transactions on Signal Processing)
Source: IEEE Transactions on Signal Processing - September 6, 2023 Category: Biomedical Engineering Source Type: research

Distributed Scaled Proximal ADMM Algorithms for Cooperative Localization in WSNs
Distributed cooperative localization in wireless networks is a challenging problem since it typically requires solving a large-scale nonconvex and nonsmooth optimization problem. In this article, we reformulate the classic cooperative localization problem as a smooth and constrained nonconvex minimization problem while its loss function is separable over nodes. By utilizing the structure of the reformulation, we propose two novel scaled proximal alternating direction method of multipliers (SP-ADMM) algorithms, which can be implemented in a distributed manner. Compared with the classic semi-definite programming relaxation t...
Source: IEEE Transactions on Signal Processing - September 6, 2023 Category: Biomedical Engineering Source Type: research

Trade-Offs in Decentralized Multi-Antenna Architectures: Sparse Combining Modules for WAX Decomposition
With the increase in the number of antennas at base stations (BSs), centralized multi-antenna architectures have encountered scalability problems from excessive interconnection bandwidth to the central processing unit (CPU), as well as increased processing complexity. Thus, research efforts have been directed towards finding decentralized receiver architectures where a part of the processing is performed at the antenna end (or close to it). A recent paper put forth an information-lossless trade-off between level of decentralization (inputs to CPU) and decentralized processing complexity (multiplications per antenna). This ...
Source: IEEE Transactions on Signal Processing - September 1, 2023 Category: Biomedical Engineering Source Type: research

Efficient-Adam: Communication-Efficient Distributed Adam
Distributed adaptive stochastic gradient methods have been widely used for large-scale nonconvex optimization, such as training deep learning models. However, their communication complexity on finding $\varepsilon$-stationary points has rarely been analyzed in the nonconvex setting. In this work, we present a novel communication-efficient distributed Adam in the parameter-server model for stochastic nonconvex optimization, dubbed Efficient-Adam. Specifically, we incorporate a two-way quantization scheme into Efficient-Adam to reduce the communication cost between the workers and server. Simultaneously, we adopt a two-way e...
Source: IEEE Transactions on Signal Processing - September 1, 2023 Category: Biomedical Engineering Source Type: research

Multichannel Frequency Estimation in Challenging Scenarios via Structured Matrix Embedding and Recovery (StruMER)
Multichannel frequency estimation with incomplete data and miscellaneous noises arises in array signal processing, modal analysis, wireless communications, and so on. In this paper, we consider maximum-likelihood(-like) optimization methods for frequency estimation in which proper objective functions are adopted subject to observed data patterns and noise types. We propose a universal signal-domain approach to solve the optimization problems by embedding the noiseless multichannel signal of interest into a series of low-rank positive-semidefinite block matrices of Hankel and Toeplitz submatrices and formulating the origina...
Source: IEEE Transactions on Signal Processing - September 1, 2023 Category: Biomedical Engineering Source Type: research

High-Dimensional Multiple-Measurement-Vector Problem: Mutual Information and Message Passing Solution
In this paper, we study the high-dimensional multiple-measurement-vector (MMV) problem, which typically arises in massive machine-type communications (mMTC) that operates with massive multiple-input multiple-output (MIMO) in a grant-free manner. We derive an expression for the mutual information (MI) of the MMV channel, considering an input that has i.i.d. rows and a row-wise output that is randomly mapped from a linear combination of the input and the weighting. Our derivation follows from the replica method, a non-rigorous but very powerful approach prevailing in physics society, but unlike the classical treatment, the r...
Source: IEEE Transactions on Signal Processing - August 31, 2023 Category: Biomedical Engineering Source Type: research

Secure Degree of Freedom of Wireless Networks Using Collaborative Pilots
This article presents novel results on SDoF of ANECE by analyzing secret-key capacity (SKC) of each pair of nodes in a network of multiple collaborative nodes per channel coherence period. Each transmission session of ANECE has two phases: phase 1 is used for pilots, and phase 2 is used for random symbols. This results in two parts of SDoF of ANECE. Both lower and upper bounds on the SDoF of ANECE for any number of users are shown, and the conditions for the two bounds to meet are given. This leads to important discoveries, including: a) The phase-1 SDoF is the same for both multi-user ANECE and pair-wise ANECE while the f...
Source: IEEE Transactions on Signal Processing - August 30, 2023 Category: Biomedical Engineering Source Type: research

Probabilistically Robust Design of Radar Waveform-Filter for Extended Target Detection in the Presence of Clutter
Assuming the stochastic model of Target Impulse Response (TIR), we address the radar waveform-filter design for extended targets with the recently proposed probabilistically robust detection criterion. The waveform-filter design is formulated as a non-convex fractional programming problem. We devise the Block Coordinate Descent (BCD) based algorithm to tackle this problem, where the waveform codes and filter are optimized alternately. It is shown that the waveforms can be optimized by sequentially checking the feasibility of a polynomial system based on the bisection method. The filter can be designed based on Semi-Definit...
Source: IEEE Transactions on Signal Processing - August 30, 2023 Category: Biomedical Engineering Source Type: research

Phase Retrieval of Quaternion Signal via Wirtinger Flow
The main aim of this paper is to study quaternion phase retrieval (QPR), i.e., the recovery of quaternion signal from the magnitude of quaternion linear measurements. We show that all $boldsymbol{d}$-dimensional quaternion signals can be reconstructed up to a global right quaternion phase factor from $boldsymbol{O(d)}$ phaseless measurements. We also develop the scalable algorithm quaternion Wirtinger flow (QWF) for solving QPR, and establish its linear convergence guarantee. Compared with the analysis of complex Wirtinger flow, a series of different treatments are employed to overcome the difficulties of the non-commutati...
Source: IEEE Transactions on Signal Processing - August 28, 2023 Category: Biomedical Engineering Source Type: research

Third-Order Nested Array: An Optimal Geometry for Third-Order Cumulants Based Array Processing
Several sparse linear array structures have recently been proposed to enhance the identifiability of direction-of-arrival estimation by using second-order or higher even-order statistics under the co-array equivalence. This paper aims to explore non-conventional odd-order statistics, namely third-order cumulants, to design a sparse linear array under the co-array equivalence for enhancing the identifiability of a given sensors array. This paper presents a mathematical framework to devise a third-order exhaustive co-array equivalence associated with third-order cumulants of the data. A novel sparse linear array geometry, na...
Source: IEEE Transactions on Signal Processing - August 28, 2023 Category: Biomedical Engineering Source Type: research