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Adaptive IMM Algorithm Based on Variational Inference for Multiple Maneuvering Extended Targets Tracking

Advances in Astronautics 2025年 1-15页

作者： Wang, Shenghua Li, Renxian Men, Chenkai Cao, Yunhe Yeo, Tat-Soon School of Communications and Information Engineering and School of Artificial Intelligence Xi’an University of Posts and Telecommunications Xi’an China National Lab of Radar Signal Processing Xidian University Xi’an China The Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore

In order to track multiple maneuvering extended targets accurately, an adaptive interacting multiple model algorithm based on variational inference (AIMM-VI) is proposed. An augmented state is constructed to cater for time-varying orientation angle and track realistic shape changes, resulting in better elliptical shape estimation and tracking accuracy. Multiple measurements from multiple extended targets are effectively assigned to corresponding targets through the marginal association probability distribution criterion, and the variational inference is used to accurately estimate the augmented state and shape information, which greatly improves the parameters estimation performance. The residual and likelihood functions are updated in real-time according to the results of variational inference, allowing for the updating of the model probability in real-time. The Markov probability transfer matrix is subsequently adaptively updated by the compression ratio, which makes the algorithm more adaptable to maneuvering target and significantly improves the adaptability and robustness of the algorithm. The final simulation and experiment results show that the proposed algorithm can effectively improve the tracking performance of multiple maneuvering extended targets.

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Image Segmentation for Improved Lossless Screen Content Compression

Image Segmentation for Improved Lossless Screen Content Comp...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Shabhrish Reddy Uddehal Tilo Strutz Hannah Och André Kaup Department of Electrical Engineering and Computer Science Coburg University Coburg Germany Multimedia Communications and Signal Processing Friedrich-Alexander University Erlangen Germany

In recent years, it has been found that screen content images (SCI) can be effectively compressed based on appropriate probability modelling and suitable entropy coding methods such as arithmetic coding. The key objective is determining the best probability distribution for each pixel position. This strategy works particularly well for images with synthetic (textual) content. However, usually screen content images not only consist of synthetic but also pictorial (natural) regions. These images require diverse models of probability distributions to be optimally compressed. One way to achieve this goal is to separate synthetic and natural regions. This paper proposes a segmentation method that identifies natural regions enabling better adaptive treatment. It supplements a compression method known as Soft Context Formation (SCF) and operates as a pre-processing step. If at least one natural segment is found within the SCI, it is split into two subimages (natural and synthetic parts) and the process of modelling and coding is performed separately for both. For SCIs with natural regions, the proposed method achieves a bit-rate reduction of up to 11.6% and 1.52% with respect to HEVC and the previous version of the SCF.

关键词： Image segmentation Adaptation models Image coding signal processing Probability distribution Entropy coding Acoustics

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IMAGE SEGMENTATION FOR IMPROVED LOSSLESS SCREEN CONTENT COMPRESSION

arXiv

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arXiv 2023年

作者： Uddehal, Shabhrish Reddy Strutz, Tilo Och, Hannah Kaup, André Department of Electrical Engineering and Computer Science Coburg University Coburg Germany Multimedia Communications and Signal Processing Friedrich-Alexander University Erlangen Germany

In recent years, it has been found that screen content images (SCI) can be effectively compressed based on appropriate probability modelling and suitable entropy coding methods such as arithmetic coding. The key objective is determining the best probability distribution for each pixel position. This strategy works particularly well for images with synthetic (textual) content. However, usually screen content images not only consist of synthetic but also pictorial (natural) regions. These images require diverse models of probability distributions to be optimally compressed. One way to achieve this goal is to separate synthetic and natural regions. This paper proposes a segmentation method that identifies natural regions enabling better adaptive treatment. It supplements a compression method known as Soft Context Formation (SCF) and operates as a pre-processing step. If at least one natural segment is found within the SCI, it is split into two sub-images (natural and synthetic parts) and the process of modelling and coding is performed separately for both. For SCIs with natural regions, the proposed method achieves a bit-rate reduction of up to 11.6% and 1.52% with respect to HEVC and the previous version of the SCF. Copyright © 2023, The Authors. All rights reserved.

关键词： Probability distributions

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Transient states to control the electromagnetic response of space-time dispersive media

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Physical Review B 2024年第23期110卷 235125-235125页

作者： Pablo H. Zapata-Cano Salvador Moreno-Rodríguez Stamatios Amanatiadis Antonio Alex-Amor Zaharias D. Zaharis Carlos Molero School of Electrical and Computer Engineering Aristotle University of Thessaloniki 54124 Thessaloniki Greece Department of Signal Theory Telematics and Communications Research Centre for Information and Communication Technologies (CITIC-UGR) Universidad de Granada 18071 Granada Spain Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia Pennsylvania 19104 USA

In this paper, we study the dynamic formation of transients when plane waves impinge on a dispersive slab that abruptly changes its electrical properties in time. The time-varying slab alternates between air and metal-like states, whose frequency dispersion is described by the Drude model. It is shown how the physics of this complex system can be well described with the joint combination of two terms: one associated with temporal refractions and the other associated with spatial refractions. To test the validity of the approach, some analytical results are compared with a self-implemented finite-difference time-domain method. Results show how the transients that occur after the abrupt temporal changes can shape the overall steady-state response of the space-time system. In fact, far from always being detrimental, these transient states can be conveniently used to perform frequency conversion or to amplify or attenuate the electromagnetic fields.

关键词： Electromagnetic transients

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Enhanced Color Palette Modeling For Lossless Screen Content Compression

Enhanced Color Palette Modeling For Lossless Screen Content ...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Hannah Och Shabhrish Reddy Uddehal Tilo Strutz André Kaup Multimedia Communications and Signal Processing Friedrich-Alexander Universität Erlangen-Nürnberg (FAU) Erlangen Germany Department of Electrical Engineering and Computer Science Coburg University of Applied Sciences and Arts Coburg Germany

Soft context formation is a lossless image coding method for screen content. It encodes images pixel by pixel via arithmetic coding by collecting statistics for probability distribution estimation. Its main pipeline includes three stages, namely a context model based stage, a color palette stage and a residual coding stage. Each subsequent stage is only employed if the previous stage can not be applied since necessary statistics, e.g. colors or contexts, have not been learned yet. We propose the following enhancements: First, information from previous stages is used to remove redundant color palette entries and prediction errors in subsequent stages. Additionally, implicitly known stage decision signals are no longer explicitly transmitted. These enhancements lead to an average bit rate decrease of 1.07% on the evaluated data. Compared to VVC and HEVC, the proposed method needs roughly 0.44 and 0.17 bits per pixel less on average for 24-bit screen content images, respectively.

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Improved Screen Content Coding in VVC Using Soft Context Formation

Improved Screen Content Coding in VVC Using Soft Context For...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

Screen content images typically contain a mix of natural and synthetic image parts. Synthetic sections usually are comprised of uniformly colored areas and repeating colors and patterns. In the VVC standard, these properties are exploited using Intra Block Copy and Palette Mode. In this paper, we show that pixel-wise lossless coding can outperform lossy VVC coding in such areas. We propose an enhanced VVC coding approach for screen content images using the principle of soft context formation. First, the image is separated into two layers in a block-wise manner using a learning-based method with four block features. Synthetic image parts are coded losslessly using soft context formation, the rest with VVC. We modify the available soft context formation coder to incorporate information gained by the decoded VVC layer for improved coding efficiency. Using this approach, we achieve Bjontegaard-Delta-rate gains of 4.98% on the evaluated data sets compared to VVC.

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A Robust Time-Domain Numerical Framework for the Spatiotemporal Variation of Graphene-Based Materials

A Robust Time-Domain Numerical Framework for the Spatiotempo...

引用

European Conference on Antennas and Propagation, EuCAP

作者： Pablo H. Zapata Cano Stamatios Amanatiadis Juan F. Valenzuela-Valdés Zaharias D. Zaharis Department of Signal Theory Telematics and Communications Research Centre for Information and Communication Technologies (CITIC-UGR) Universidad de Granada Granada Spain School of Electrical and Computer Engineering Aristotle University of Thessaloniki (AUTH) Thessalonikik Greece

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

Space-time metamaterials have gained considerable interest for their dynamism and potential for wave manipulation and control. Externally tunable materials such as graphene constitute an interesting alternative to come up with practical realizations of spatiotemporally modulated devices. In this work, we present a time-domain numerical framework that allows to simulate space-time modulation scenarios with graphene layers. The proposed algorithm is described and some scenarios including the periodical modulation of graphene's conductivity are discussed.

关键词： Graphene Modulation Europe Conductivity Metamaterials Spatiotemporal phenomena Numerical models Time-domain analysis Dispersion Finite difference methods

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Multi-Task Sparse signal Recovery with Dirichlet Process Priors Based on Expectation Propagation Technique 7

Multi-Task Sparse Signal Recovery with Dirichlet Process Pri...

引用

7th International Conference on signal and Image processing, ICSIP 2022

作者： Fu, Yin Wu, Qisong Zhang, Yimin D. Amin, Moeness G. Southeast University Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education Nanjing210096 China Temple University Department of Electrical and Computer Engineering PhiladelphiaPA19122 United States Villanova University Center for Advanced Communications VillanovaPA19085 United States

ISBN: (数字)9781665495639

ISBN: (纸本)9781665495639

Exploiting the shared information among tasks to significantly improve the sparse reconstruction performance lays the essence of multi-task compressive sensing. In this paper, a novel generative model of multi-task compressive sensing with Dirichlet process (DP) priors is proposed and the sharing mechanisms among tasks are revealed, yielding a principled means of inferring the clusters as well as performing compressive sensing inversion simultaneously. The spike-and-slab priors are first used to model the group sparsity among tasks within the identical cluster, and the DP priors are then introduced to automatically perform clustering for the tasks. The expectation propagation method is finally carried out to take the inference for posterior distribution approximation. The superiority of the proposed method over state-of-the-art algorithms is demonstrated by using experimental results on both numerical data and real data sets. © 2022 IEEE.

关键词： Compressed sensing

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Adaptive Sparse Gaussian Process

arXiv

引用

arXiv 2023年

作者： Gómez-Verdejo, Vanessa Parrado-Hernández, Emilio Martínez-Ramón, Manel Signal Processing and Communications Department University Carlos III de Madrid Leganés Madrid28911 Spain Electrical and Computer Engineering Department The University of New Mexico AlbuquerqueNM87106 United States

Adaptive learning is necessary for non-stationary environments where the learning machine needs to forget past data distribution. Efficient algorithms require a compact model update to not grow in computational burden with the incoming data and with the lowest possible computational cost for online parameter updating. Existing solutions only partially cover these needs. Here, we propose the first adaptive sparse Gaussian Process (GP) able to address all these issues. We first reformulate a variational sparse GP algorithm to make it adaptive through a forgetting factor. Next, to make the model inference as simple as possible, we propose updating a single inducing point of the sparse GP model together with the remaining model parameters every time a new sample arrives. As a result, the algorithm presents a fast convergence of the inference process, which allows an efficient model update (with a single inference iteration) even in highly non-stationary environments. Experimental results demonstrate the capabilities of the proposed algorithm and its good performance in modeling the predictive posterior in mean and confidence interval estimation compared to state-of-the-art approaches. © 2023, CC BY.

关键词： Gaussian distribution

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Unifying Privacy Measures via Maximal (α, β)-Leakage (MαbeL)

arXiv

引用

arXiv 2023年

作者： Gilani, Atefeh Kurri, Gowtham R. Kosut, Oliver Sankar, Lalitha The School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85281 United States The School of Electrical Computer and Energy Engineering Arizona State University United States The Signal Processing and Communications Research Centre International Institute of Information Technology Telangana Hyderabad500032 India

We introduce a family of information leakage measures called maximal (α, β)-leakage (MαbeL), parameterized by real numbers α and β greater than or equal to 1. The measure is formalized via an operational definition involving an adversary guessing an unknown (randomized) function of the data given the released data. We obtain a simplified computable expression for the measure and show that it satisfies several basic properties such as monotonicity in β for a fixed α, non-negativity, data processing inequalities, and additivity over independent releases. We highlight the relevance of this family by showing that it bridges several known leakage measures, including maximal αleakage (β = 1), maximal leakage (α = ∞, β = 1), local differential privacy (LDP) (α = ∞, β = ∞), and local Rényi differential privacy (LRDP) (α = β), thereby giving an operational interpretation to local Rényi differential privacy. We also study a conditional version of MαbeL on leveraging which we recover differential privacy and Rényi differential privacy. A new variant of LRDP, which we call maximal Rényi leakage, appears as a special case of MαbeL for α = ∞ that smoothly tunes between maximal leakage (β = 1) and LDP (β = ∞). Finally, we show that a vector form of the maximal Rényi leakage relaxes differential privacy under Gaussian and Laplacian mechanisms. Copyright © 2023, The Authors. All rights reserved.

关键词： Data handling

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