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Multistage Multirate Filterbank for FPGA Resource Optimization

IEEE EMBEDDED SYSTEMS LETTERS 2024年第3期16卷 259-262页

作者： Arnaldi, L. H. Bariloche Atom Ctr Lab Detecc Particulas & Radiac R8402AGP San Carlos De Bariloche Argentina Natl Commiss Atom Energy Inst Balseiro R8402AGP San Carlos De Bariloche Argentina

In this letter, the problem of optimization of multirate filterbanks is addressed. The factors that define the efficiency of these multirate systems are investigated and the implementations of structures in stages are analyzed. The latter, together with the polyphase implementations of the filters, allows obtaining optimal filterbanks in the use of resources for the FPGAs.

关键词： Passband Finite impulse response filters filtering theory Filter banks Field programmable gate arrays filtering algorithms Cost function Filterbank multirate multistage optimization

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On the Privacy of Multi-Versioned Approximate Membership Check Filters

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IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING 2024年第4期21卷 1981-1993页

作者： Reviriego, Pedro Sanchez-Macian, Alfonso Dillinger, Peter C. Walzer, Stefan Univ Politecn Madrid Madrid 28040 Spain Univ Carlos III Madrid Madrid 28903 Spain Meta Platforms Inc Seattle WA 98004 USA Univ Cologne D-50923 Cologne Germany

Approximate membership filters are increasingly used in many computing and networking applications and new filter designs are being continuously presented to improve one or more performance metrics. Therefore, understanding their security and privacy is an important issue. Previous works have considered attackers that only have access to an individual filter in isolation. For applications that generate many related filters, such as a filter for a deny list that evolves over time, that analysis is insufficient. This article considers an attacker with access to several versions of a filter that share most of the same input elements. We find that for typical implementations of Bloom, cuckoo, and quotient filters, the attacker gains little or no advantage with access to multiple versions of a filter. However, typical xor filters do reveal more information about their input elements by querying multiple versions of a filter, and we propose techniques to enhance the privacy of xor filters and others.

关键词： Information filters Fingerprint recognition Privacy Matched filters Metadata filtering algorithms Analytical models approximate membership checking Bloom filters Cuckoo filters Quotient filters Xor filters

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Incipient Fault Identification of Bearings in Electric Drive System Under Varying Speeds Based on Adaptive Feature Mode Decomposition

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IEEE SENSORS JOURNAL 2025年第9期25卷 15975-15995页

作者： Wang, Chaoge Tian, Xinyu Zhou, Funa Wang, Ran Li, Hongkun Shanghai Maritime Univ Sch Logist Engn Shanghai 201306 Peoples R China Dalian Univ Technol Sch Mech Engn Dalian 116024 Peoples R China

Rolling bearings constitute a core component in the electric drive system of electric vehicles, and their health status is crucial for the safe operation of these vehicles. Therefore, effective condition monitoring and fault detection for bearings is of paramount importance. However, under variable operating conditions, the incipient weak fault signatures of bearings are prone to be masked by intense noise, significantly increasing the challenge of fault identification. To tackle this issue, an adaptive feature mode decomposition (AFMD) approach is introduced for diagnosing incipient weak fault in bearings under variable operating conditions. First, the instantaneous rotational frequency is extracted from the motor stator current signal. Subsequently, angular domain resampling is performed on the synchronously sampled vibration signal. Second, to overcome the lack of adaptability in determining the key input parameters of the FMD algorithm, which typically relies on repeated manual trials based on experience, this research proposes determining the number of decomposition modes through scale-space spectral segmentation. On this basis, the spectral Gini index (SGI) is adopted as the objective function, and the particle swarm optimization (PSO) is utilized to automatically ascertain the filter number and filter length. With the optimal decomposition parameter combination, the AFMD is employed to perform optimal mode decomposition on the obtained angular domain bearing signal, and the component exhibiting the highest SGI value is chosen as the sensitive mode. Finally, significant fault characteristic orders are extracted from the envelope order spectrum (EOS) of the sensitive component to accurately identify the fault type. The efficacy and superiority of the proposed methodology are confirmed through variable-speed simulated bearing signal, experimental data, and actual electric vehicle bearing diagnosis cases. The analysis demonstrates that the proposed approach can c

关键词： Vibrations Fault diagnosis Rolling bearings Noise Electric vehicles Accuracy filtering algorithms Finite impulse response filters Filter banks Feature extraction feature mode decomposition (FMD) incipient fault identification rolling bearing variable speed

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32-Gb/s CAP Signals Wireless Delivery at D-Band Over 4.6 Km Based on Photonics-Aided Technology and Envelope Detection

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JOURNAL OF LIGHTWAVE TECHNOLOGY 2024年第14期42卷 4809-4817页

作者： Yang, Xiongwei Zhou, Wen Zhao, Xianming Yu, Jianjun Wei, Yi Wang, Mingxu Zhang, Qiutong Tan, Jingwen Han, Yang Tian, Peng Li, Weiping Zhang, Bing Zhao, Feng Uddin, Rehim Zhang, Ying Wang, Kaihui Fudan Univ State Key Lab ASIC & Syst Key Lab Informat Sci Electromagnet Waves MoE Shanghai 200433 Peoples R China Fudan Univ Sch Informat Sci & Technol Shanghai 200433 Peoples R China Harbin Inst Technol Harbin 150006 Peoples R China Xian Univ Posts & Telecommun Sch Automat Xian 710121 Peoples R China Shanghai Univ Shanghai 200444 Peoples R China

The Carrier-less Amplitude and Phase (CAP) modulation is an advanced modulation technology with the advantages of high spectrum utilization, low cost, and low complexity. In this paper, based on photonics-aided technology and envelope detection, we experimentally demonstrate the wireless transmission of 4.6 km of 8Gbaud CAP-4QAM signal and 1.2 km of 5Gbaud CAP-16QAM signal over D-band at 125GHz, respectively. At the same time, combined with antenna polarization multiplexing technology, the maximum bit rate can reach 32 Gb/s and 40 Gb/s, respectively. Both BERs are below the 25% overhead soft-decision forward error correction (SD-FEC) threshold of 4.2x10(-2). In addition, in the back-end equalization algorithm processing, we compared the time domain (TD) constant module algorithm (CMA), the Decision Directed Least Mean Squares (DDLMS) algorithm of the time domain multiple input multiple output (MIMO) structure, the frequency domain (FD) CMA algorithm, and the FD MIMO-DDLMS algorithm. The results show that the FD MIMO DDLMS algorithm can effectively compensate for the I/Q imbalance problem of CAP signals while maintaining low computational complexity. As far as we know, this is the first experimental demonstration of a rate exceeding 30 Gb/s in a D-band long-distance transmission system with envelope detection, which provides an effective solution for low-cost millimeter wave transmission.

关键词： Modulation Wireless communication Matched filters Time-domain analysis Photonics filtering algorithms Adaptive filters CAP modulation D-band envelope detection photonics-aided technology time/frequency domain equalization

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Outlier-Aware Recursive Instantaneous Minimum Error Entropy Algorithm

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2025年第6期55卷 4076-4090页

作者： Zhong, Shan Peng, Bei Wang, Ziyi He, Jiacheng Zhang, Kun Wang, Gang Univ Elect Sci & Technol China Sch Mech & Elect Engn Chengdu 611731 Peoples R China Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu 611731 Peoples R China

The minimum error entropy (MEE) criterion closely relies on the quadratic information potential (QIP) estimates of Renyi's entropy. Nevertheless, the conventional obtained QIP estimates are numerically unstable, especially when the error samples contain outliers, resulting in the optimal solution of the MEE criterion deviating from the target vector to a certain extent. To address this problem, we introduce the M-estimate method from robust statistics into the QIP estimation process;thus, a robust estimation method called instantaneous M-estimate QIP (IM-QIP) is proposed, and several important properties of IM-QIP are presented. The proposed IM-QIP estimates could be implemented simply while ensuring great robustness. Naturally, we further propose the corresponding instantaneous M-estimate MEE (IM-MEE) criterion and apply it to adaptive filtering. A robust recursive adaptive filtering algorithm, called the recursive IM-MEE (RIM-MEE) algorithm, is proposed and analyzed in this article, along with its stability and theoretical steady-state performance. Additionally, we demonstrate that the RIM-MEE algorithm achieves a smaller theoretical bound compared to the traditional MEE algorithm under heavy-tailed and skewed noise conditions. The simulation results revealed the robustness of the IM-QIP estimates and verified the theoretical expectations and superior performance of the RIM-MEE algorithm.

关键词： Estimation Signal processing algorithms Entropy Noise filtering Robustness Stability criteria filtering algorithms Probability density function Numerical stability M-estimate minimum error entropy (MEE) quadratic information potential (QIP) recursive adaptive filtering Renyi's entropy

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Low Computational Complexity Delay Estimation Algorithm for Digital Predistortion

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2024年第7期71卷 3548-3552页

作者： Zhong, Tianyang Peng, Jun He, Songbai You, Fei Guo, Junfu Wang, Xinyu Tang, Yijie He, Guo Univ Elect Sci & Technol China Sch Elect Sci & Engn Chengdu 611731 Peoples R China

In practical scenarios, digital predistortion (DPD) systems are typically deployed on hardware platforms. However, the current time delay alignment algorithm, a critical component of DPD processing, requires substantial hardware resource allocation. Consequently, this brief introduces a novel delay estimation algorithm aimed at simplifying the time alignment segment, including both integer and fractional elements. The integer alignment method is established on an adaptive filter framework, while the fractional component leverages a recursive least square (RLS) algorithm, based on a Farrow structure, to circumvent extensive matrix calculations. The complexity analysis, coupled with experimental results show that the proposed methods not only preserve high accuracy but also substantially diminish computational resource demands by 88.7% and 87.8%, respectively, when compared with two prevailing delay estimation techniques. This enhancement notably augments the performance of hardware-based DPD systems.

关键词： Delay estimation Adaptive filters Finite impulse response filters Time-domain analysis Predistortion Hardware filtering algorithms Digital predistortion (DPD) time synchronization time domain farrow structure

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Distribution-Based Determination of Sparse Secondary Path for Active Noise Control

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2024年第7期71卷 3583-3587页

作者： Guo, Xinnian Jiang, Jean Tan, Lizhe Suqian Univ Jiangsu Prov Engn Res Ctr Smart Poultry Farming & Suqian 2238005 Peoples R China Purdue Univ Northwest Coll Technol Hammond IN 46323 USA Purdue Univ Northwest Dept Elect & Comp Engn Hammond IN 46323 USA

The sparse secondary path model notably enhances the computational efficiency of active noise control (ANC) system. However, there is no specific rule for determining the sparse secondary coefficients. In this brief, we propose a distribution-based method for the selection of sparse threshold for determination of coefficients in secondary path modeling. To offer guidance on the selection of sparse coefficients, a power function of the sparse threshold is defined and the analytical solution is derived based on Laplacian and Gaussian distributions for secondary coefficients. The effectiveness of selected sparse coefficients in representing the secondary path is verified by computer simulations and real duct ANC experiments for control of narrowband and broadband noise.

关键词： Finite impulse response filters Computational modeling Mathematical models filtering algorithms Laplace equations Microphones Kernel Active noise control finite impulse response sparse secondary path Laplacian distribution

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Joint Transmit-Receive Filter Design With Lower APSL and ICPL to Suppress Interference

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2024年第3期60卷 3673-3687页

作者： Zuo, Lei Lan, Zhengyu Lu, Xiaofei Gao, Yongchan Mao, Linlin Xidian Univ Natl Key Lab Radar Signal Proc Xian 710071 Peoples R China Jiuquan Satellite Launch Ctr Jiuquan 735000 Peoples R China Xidian Univ Dept Elect Engn Xian 710071 Peoples R China Chinese Acad Sci Inst Acoust Beijing 100045 Peoples R China

For weak target detection and interference suppression, we consider a joint design of transmit waveform and space-time receive filter to reduce the waveform autocorrelation peak sidelobe level and interference cross-correlation peak level. First, we propose a design criterion, which formulates the multi-L-p norm and signal-interference-noise-ratio model under the constraints of waveform and mismatched filter to suppress digital radio frequency memory interference. Second, we present an iterative penalty majorization-minimization (IPMM) algorithm to solve the multi-L-p norm nonconvex optimization problem. Finally, a majorization peak sidelobe level model is proposed, which enhances the convergence speed of the IPMM algorithm. Numerical results show that the proposed approach has a better performance and higher computational speed than conventional ones.

关键词： Interference Signal to noise ratio filtering algorithms Numerical models Optimization Object detection Band-pass filters Autocorrelation peak sidelobe level (PSL) cross-correlation peak level (CPL) interference suppression waveform design

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A Novel Set-Member Filter for Maneuver Non-Ellipsoid Extended Target Tracking With Unknown but Bounded Noises

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IEEE SENSORS JOURNAL 2025年第8期25卷 13708-13718页

作者： Ma, Tianli Sun, Hanying Wang, Kexin Chen, Chaobo Xian Technol Univ Autonomous Syst & Intelligent Control Int Joint Re Xian 710021 Peoples R China Xian Technol Univ Sch Elect Informat Engn Xian 710021 Peoples R China

For non-ellipsoid extended target tracking, the process disturbances and measurement noises are described by independent random variables, i.e., Gaussian distribution. In many real scenarios, however, the disturbances and noises are completely unknown except for bounds. This article proposes a novel set-member filter for maneuver non-ellipsoid extended target tracking with unknown but bounded (UBB) noise. The non-ellipsoid extent of the extended target is described by the random hypersurface model (RHM), the predicted state and shape parameters are obtained by calculate the Minkowski sum of the ellipsoids of the state and shape parameters and UBB noises, respectively. At the measurement update stage, the predicted shape parameters are modified based on the maneuver angle, and the minimal ellipsoid containing the pseudo-measurement nonlinear function is calculated by solving the semi-positive definite programming problem, in which the trace of the shape matrix of the pseudo-measurement nonlinear function is as the objective function. The update shape parameters are updated by calculating the intersection set of predicted shape ellipsoid and the minimal pseudo-measurement ellipsoid. An evaluation of performance in a simulated environment shows that the proposed SMF-NEET approach outperforms the existing adaptive extended Kalman filter based on a RHM (RHM-AEKF) and unscented Kalman filter based on the random hypersurface model (RHM-UKF) methods with up to 83.9% and 88.9% improvement in the accuracy in position, 40.3% and 58.2% in velocity, 26.6% and 31.5% in the shape, respectively, while tracking a maneuver non-ellipsoid extend target with UBB Noises.

关键词： Shape Noise Ellipsoids Target tracking Kinematics Noise measurement Shape measurement Kalman filters filtering algorithms Antenna measurements Extended target non-ellipsoid extension random hypersurface model (RHM) semi-positive definite programming set-member filter unknown but bounded (UBB) noises

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Channel Pruning of Transfer Learning Models Using Novel Techniques

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IEEE ACCESS 2024年 12卷 94914-94925页

作者： Thaker, Pragnesh Mohan, Biju R. Natl Inst Technol Karnataka Srinivasnagar Surathkal 575025 Karnataka India

This research paper delves into the challenges associated with deep learning models, specifically focusing on transfer learning. Despite the effectiveness of widely used models such as VGGNet, ResNet, and GoogLeNet, their deployment on resource-constrained devices is impeded by high memory bandwidth and computational costs, and to overcome these limitations, the study proposes pruning as a viable solution. Numerous parameters, particularly in fully connected layers, contribute minimally to computational costs, so we focus on convolution layers' pruning. The research explores and evaluates three innovative pruning methods: the Max3 Saliency pruning method, the K-Means clustering algorithm, and the Singular Value Decomposition (SVD) approach. The Max3 Saliency pruning method introduces a slight variation by using the three maximum values of the kernel instead of all nine to compute the saliency score. This method is the most effective, substantially reducing parameter and Floating Point Operations (FLOPs) for both VGG16 and ResNet56 models. Notably, VGG16 demonstrates a remarkable 46.19% reduction in parameters and a 61.91% reduction in FLOPs. Using the Max3 Saliency pruning method, ResNet56 shows a 35.15% reduction in parameters and FLOPs. The K-Means pruning algorithm is also successful, resulting in a 40.00% reduction in parameters for VGG16 and a 49.20% reduction in FLOPs. In the case of ResNet56, the K-Means algorithm achieved a 31.01% reduction in both parameters and FLOPs. While the Singular Value Decomposition (SVD) approach provides a new set of values for condensed channels, its overall pruning ratio is smaller than the Max3 Saliency and K-Means methods. The SVD pruning method prunes 20.07% parameter reduction and a 24.64% reduction in FLOPs achieved for VGG16, along with a 16.94% reduction in both FLOPs and parameters for ResNet56. Compared with the state-of-the-art methods, the Max3 Saliency and K-Means pruning methods performed better in Flops reduction m

关键词： Computational modeling Convolutional neural networks Kernel Clustering algorithms Accuracy Transfer learning filtering algorithms Deep compression of CNN channel pruning structured pruning neural network compression transfer learning

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