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On Searching All Solutions of Microwave Filter Synthesis Based on Interval Arithmetic

IEEE MICROWAVE AND WIRELESS TECHNOLOGY LETTERS 2023年第6期33卷 811-814页

作者： Zeng, Yi Yu, Ming Southern Univ Sci & Technol Shenzhen Key Lab EM Informat Shenzhen 518055 Peoples R China Southern Univ Sci & Technol Dept Elect & Elect Engn Shenzhen 518055 Peoples R China

In this letter, the numerical interval Newton algorithm (NINA) is introduced into coupling matrix (CM) synthesis (reconfiguration) for the first time. In particular, all existing real solutions to microwave filter CM can be found with mathematical certainty, which provides designers with the flexibility to select the most suitable configuration. Also, CM limits can be directly imposed in the synthesis process to only compute solutions in the specified range. This synthesis process is independent of initial variable values, and the global convergence is theoretically guaranteed. Moreover, NINA is a deterministic method that can verify the existence or nonexistence, uniqueness or non-uniqueness of a given CM topology with the desired filtering performance. Furthermore, the processes dealing with both well-determined and over-determined systems are discussed to cover the synthesis of CMs with diverse configurations. One practical sixth-order dielectric filter with parasitic couplings is exemplified to validate the effectiveness of the presented synthesis approach.

关键词： Microwave filters Topology Couplings Mathematical models Arithmetic Newton method filtering algorithms All solutions coupling matrix (CM) filter synthesis interval arithmetic

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Novel Deep Hybrid and Ensemble algorithms for Improving GPS Navigation Positioning Accuracy

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IEEE ACCESS 2023年 11卷 53518-53530页

作者： Aydin, Tolga Erdem, Ebru Ataturk Univ Dept Comp Engn TR-25240 Erzurum Turkiye

GPS (Global Positioning System) has been a widespread system used for various purposes in today's world and it is essential to suggest innovative effective solutions to improve its use and functions. The present study proposes GPS coordinate conversion models based on Machine Learning (ML) and Deep Learning (DL) algorithms in order to "improve accuracy of GPS conversion and positioning services". 23 different models are tested on two different data sets to achieve this purpose. The study primarily aims to improve positioning accuracy of navigation systems by using GPS data through hybrid and ensemble algorithms. The proposed DL-based models are named as GPSCNNs and GPSLSTM. GPSCNNs contain "Xception, VGG16, VGG19, Alexnet, CNN1, CNN2, CNN3" deep learning algorithms in their structure. Of these algorithms, "Xception, VGG16, VGG19, Alexnet" are pre-trained models. "CNN1" consists of 2 Convolution, 2 Average Pool, 1 Flatten, and 5 Dense layers. "CNN2" consists of 1 Convolution, 1 Max Pool, 1 Flatten, and 4 Dense layers. "CNN3" consists of 4 Convolution, 4 Batch Normalization, 2 Max Pool, 1 Flatten, and 3 Dense layers. GPSLSTM contains 1 LSTM and 1 Dense layer in its structure. Raw GPS data are fed into the models as input, which was followed by obtaining information about the features of the data and getting coordinate data as input. The results show that ensemble models provide the most accurate positioning and GPSCNNs and GPSLSTM were quite promising in boosting this accuracy.

关键词： Global Positioning System Predictive models Data models Stacking Kalman filters Wiener filters filtering algorithms Ensemble algorithms GPS GPSCNNs GPSLSTM

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Joint Design of Waveform and Mismatched Filter for Interrupted Sampling Repeater Jamming Suppression

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2023年第6期59卷 8037-8050页

作者： Gao, Yuhang Fan, Huayu Ren, Lixiang Liu, Zihao Liu, Quanhua Mao, Erke Beijing Inst Technol Sch Informat & Elect Radar Res Lab Beijing 100081 Peoples R China Beijing Inst Technol Minist Educ Key Lab Elect & Informat Technol Satellite Nav Beijing 100081 Peoples R China Beijing Inst Technol Chongqing Innovat Ctr Chongqing 401120 Peoples R China

The interrupted sampling repeater jamming (ISRJ) produces multiple false targets after pulse compression, making it difficult for radar to detect real targets. In this article, an anti-ISRJ algorithm is developed based on the joint design of the waveform and the mismatched filter with an expanded mainlobe. First, to prevent false alarms when the range sidelobes and jamming peaks of the filter output are too high, the sum of the peak sidelobe level of the waveform compressed with the mismatched filter and the peak level of the ISRJ signal compressed with the mismatched filter is taken as an optimization criterion for minimization. Meanwhile, a penalty function is used to control the mainlobe shape of the correlation function between the waveform and the mismatched filter to approximate the desired mainlobe. To maximize the transmitted power efficiency of the radar and control the signal-to-noise ratio loss caused by the mismatched filter, a constant modular constraint for the waveform and an energy constraint for the filter are adopted. Then, an iterative algorithm based on the majorization-minimization framework is proposed to solve the joint design problem. In each iteration, an analytical expression is derived to realize the simultaneous updating of the waveform and filter. The convergence of the proposed algorithm is proven, and its computational complexity is analyzed. Finally, simulations are provided to demonstrate the effectiveness of the proposed algorithm. Compared with existing algorithms, the waveform and filter designed in this article exhibit better pulse compression performance and antijamming ability.

关键词： filtering algorithms Optimization Jamming Correlation Band-pass filters Radar detection Information filters Expanded mainlobe interrupted sampling repeater jamming (ISRJ) jamming peak joint design of waveform and mismatched filter majorization-minimization (MM)

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MOV-Modified-FxLMS Algorithm With Variable Penalty Factor in a Practical Power Output Constrained Active Control System

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IEEE SIGNAL PROCESSING LETTERS 2023年 30卷 723-727页

作者： Lai, Chung Kwan Shi, Dongyuan Lam, Bhan Gan, Woon-Seng Nanyang Technol Univ NTU Sch Elect & Elect Engn Singapore 639798 Singapore

Practical Active Noise Control (ANC) systems typically require a restriction in their maximum output power, to prevent overdriving the loudspeaker and causing system instability. Recently, the minimum output variance filtered-reference least mean square (MOV-FxLMS) algorithm was shown to have optimal control under output constraint with an analytically formulated penalty factor, but it needs offline knowledge of disturbance power and secondary path gain. The constant penalty factor in MOV-FxLMS is also susceptible to variations in disturbance power that could cause output power constraint violations. This letter presents a new variable penalty factor that utilizes the estimated disturbance in the established Modified-FxLMS (MFxLMS) algorithm, resulting in a computationally efficient MOV-MFxLMS algorithm that can adapt to changes in disturbance levels in real-time. Numerical simulation with real noise and plant response showed that the variable penalty factor always manages to meet its maximum power output constraint despite sudden changes in disturbance power, whereas the fixed penalty factor has suffered from a constraint mismatch.

关键词： Signal processing algorithms Finite impulse response filters Power generation filtering algorithms Power amplifiers Optimal control Convergence Active noise control (ANC) output power constraint Index Terms minimum output variance (MOV) modified filtered reference least mean square (Modified-FxLMS) algorithm

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Advanced Iterative Synthesis of Equiripple Dual-Band Filters With Fully Prescribed Performance

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IEEE MICROWAVE AND WIRELESS TECHNOLOGY LETTERS 2023年第9期33卷 1255-1257页

作者： Ren, Xiaohui He, Yuxing Sun, Liguo Univ Sci & Technol China Dept EE & Informat Sci Hefei 230027 Peoples R China Southwest Jiaotong Univ Sch Informat Sci & Technol SIST Chengdu 611756 Peoples R China

In this letter, an iterative method is presented to synthesize equiripple dual-band filters with fully prescribed in-and out-band performance. The synthesis relies on an improved Remez algorithm where respective ripple factors are introduced for the two given passbands. As a result, an equiripple response can be achieved within each passband, and their return loss (RL) (i.e., RL1 and RL2 levels can be different and controllable by setting the ratio of the ripple factors. Note that an extra transmission zero (TZ) is thus generated and adjustable based on the RL ratio, whose location is more flexible (to prevent locating inside of a passband) when compared with previous works. To demonstrate the effectiveness of the presented method, we provide and discuss two synthetic examples with various filter functions, and obtain desired results.

关键词： Passband filtering theory Microwave filters Dual band Band-pass filters filtering algorithms Couplings Dual-band filter filter synthesis polynomial approximation

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PGSim: Efficient and Privacy-Preserving Graph Similarity Query Over Encrypted Data in Cloud

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IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2023年 18卷 2030-2045页

作者： Zheng, Yandong Zhu, Hui Lu, Rongxing Guan, Yunguo Zhang, Songnian Wang, Fengwei Shao, Jun Li, Hui Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China Henan Key Lab Network Cryptog Technol Zhengzhou 450000 Peoples R China Univ New Brunswick Fac Comp Sci Fredericton NB E3B 5A3 Canada Zhejiang Gongshang Univ Sch Comp & Informat Engn Hangzhou 310018 Peoples R China

The boom of cloud computing has stimulated the prevalence of outsourced query services, and privacy concerns further motivate extensive studies on privacy-preserving queries in the cloud. Graph similarity query is one critical query type, in which the similarity between two graphs is usually measured by graph edit distance (GED). Although many schemes have been proposed for GED computation/graph similarity query, they do not consider data privacy and are not applicable to the cloud computing scenario. To address this issue, in this paper, we propose the first efficient and privacy-preserving graph similarity query (PGSim) scheme in the filter and verification framework. Specifically, we first identify the pivot filter property of GED and use the property to design a pivot R-tree based filter algorithm, which can efficiently retrieve candidate graphs for graph similarity query. Then, we design a vertex mapping (VM) tree to index all vertex mappings between two graphs and develop a GED query verification algorithm to verify candidate graphs. After that, we design a suite of private algorithms based on a symmetric homomorphic encryption scheme and apply them to propose a pivot R-tree based filter predicate encryption (PRFilter) scheme and a private GED query verification (PGQVerify) algorithm. Based on the PRFilter scheme and the PGQVerify algorithm, we propose our PGSim scheme. Rigorous security analysis shows that our scheme is selectively secure. Performance evaluation also demonstrates the high efficiency of our scheme.

关键词： filtering algorithms Costs Cloud computing Data privacy Indexes Servers Privacy Graph similarity query graph edit distance pivot R-tree privacy preservation

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Robust Subband Adaptive Filter algorithms-Based Mixture Correntropy and Application to Acoustic Echo Cancellation

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IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 2023年 31卷 1223-1233页

作者： Zhao, Haiquan Gao, Yuan Zhu, Yingying Southwest Jiaotong Univ Key Lab Magnet Suspens Technol & Maglev Vehicle Minist Educ Chengdu 610031 Peoples R China Southwest Jiaotong Univ Sch Elect Engn Chengdu 610031 Peoples R China

To acquire an improvement of the performance of the subband adaptive filter with impulsive interference, the normalized subband adaptive filter (NSAF) algorithm-based maximum correntropy criterion (MCC), called MCC-NSAF, has been developed. However, it is hard for the MCC criterion to take into account both the fast convergence rate and low steady-state error with a fixed kernel bandwidth. To handle this dilemma, in this paper, the normalized subband adaptive filter algorithm-based maximum mixture correntropy criterion (MMC) algorithm, called MMC-NSAF, is proposed. The MMC-NSAF algorithm integrates two correntropies with complementary control sizes of Gaussian kernel and can not only converge quickly but also has a small misalignment. Yet the MMC-NSAF still has some limitations because of its fixed step size. Therefore, a convexly combined MMC-NSAF algorithm, namely MMC-CNSAF, is proposed. The MMC-CNSAF algorithm utilizes two Gaussian kernels of different size and can combine overall improvement between convergence rate and steady-state error simultaneously. Eventually, the convergence and the computational complexity are analyzed. To achieve the test and verification of the robustness of proposed algorithms, simulations are carried out to discuss the effect of the parameters algorithm under colored input signals in impulsive interference environments for system identification. Meanwhile, the performances of the proposed algorithms under the influence of the acoustic echo cancellation in practical application are studied.

关键词： Adaptive filters Kernel filtering algorithms Convergence Steady-state Interference Acoustics Acoustic echo cancellation Convex combination impulsive interference mixture correntropy subband adaptive filter

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Channel Estimator and Symbol Detector for OTFS Systems Impaired by Impulsive Noise

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IEEE COMMUNICATIONS LETTERS 2023年第10期27卷 2742-2746页

作者： Kumar, Ajay Jain, Sandesh Majhi, Sudhan Indian Inst Sci Dept Elect Commun Engn Bengaluru 560012 India Atal Bihari Vajpayee Indian Inst Informat Technol Dept Elect & Elect Engn Gwalior 474015 India

The most widely used conventional message-passing detector (MPD) requires channel state information and delivers suboptimal performance for orthogonal time frequency space (OTFS) systems in the presence of impulsive noise (IN). To circumvent this limitation, in this letter, we propose a novel l(0)-norm constrained maximum Versoria criterion (l(0) -MVC) based channel estimator for the OTFS systems impaired by IN with an optimal adaptive tuning of the sparsity regularization parameter. Furthermore, we propose a robust message-passing based on the maximum Versoria criterion (MP-MVC) for OTFS symbol detection in the presence of IN. Analytical and simulation results indicate that the proposed $l_{0}$ -MVC channel estimator and MP-MVC symbol detector outperforms the existing state-of-the-art approaches.

关键词： Symbols Channel estimation Detectors Manganese Quadrature amplitude modulation Sparse matrices filtering algorithms OTFS sparse channel estimation symbol detector non-Gaussian noise maximum versoria criterion

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Median Autoregressive Graph Filters

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IEEE SIGNAL PROCESSING LETTERS 2023年 30卷 833-837页

作者： Tay, David B. Deakin Univ Sch IT Waurn Ponds Vic 3216 Australia

Graph filters are fundamental for extracting and processing signals defined over irregular domains. Most graph filters in the literature are linear, and are usually based on polynomials of the graph shift matrix. Autoregressive Moving Average (ARMA) graph filters are a generalization of polynomial filters, but are still linear. In this work, we propose a nonlinear graph filter that is an extension of the order one ARMA graph filter, to give the Median Autoregressive Graph Filter (MAF). The proposed MAF has a similar localization property to the linear counterpart, and can be implemented in a distributive manner. Though strictly nonlinear, the MAF has some linear-like properties, which will be formally proven in this work. Application of the proposed MAF to the denoising of real-world sensor network datasets will be presented. Comparisons with the linear counterpart will also be made.

关键词： Nonlinear filters Maximum likelihood detection IIR filters Finite impulse response filters Low-pass filters filtering algorithms Noise reduction Autoregressive filter graph filter Index Terms median filter nonlinear filter

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A Bias-Compensated NMMCC Algorithm Against Noisy Input and Non-Gaussian Interference

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2023年第9期70卷 3689-3693页

作者： Long, Xiaoqiang Zhao, Haiquan Hou, Xinyan Southwest Jiaotong Univ Sch Elect Engn Minist Educ Chengdu 610031 Peoples R China Southwest Jiaotong Univ Key Lab Magnet Suspens Technol & Maglev Vehicle Minist Educ Chengdu 610031 Peoples R China

This brief proposes a bias-compensated normalized adaptive filtering algorithm (BC-NMMCC) under the mixture maximum correntropy (MMCC), which can increase the flexibility of the correntropy by changing the weight of the mixture parameter, as well as change the mixture kernel function to a single kernel function when the mixture parameter takes endpoint value. In order to deal with the case of noisy input and non-Gaussian noise interference, a bias-compensated term is obtained by utilizing an unbiased criterion and some assumptions to increase the robustness of the NMMCC algorithm. To further improve the performance of the proposed algorithm, a modified parameter is added to the bias-compensated term. Then, the computational complexity of the proposed algorithm is analyzed. Finally, the numerical simulation results also show that the BC-NMMCC algorithm performs better in terms of convergence speed and steady-state performance than several other existing algorithms with better robustness under different noise disturbances.

关键词： Signal processing algorithms Kernel Estimation Interference Robustness Noise measurement filtering algorithms Adaptive filtering mixture maximum correntropy mixture parameter modified parameter

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