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Fast ramp fraction loss SVM classifier with low computational complexity for pattern classification

NEURAL NETWORKS 2025年 184卷 107087页

作者： Wang, Huajun Li, Wenqian Changsha Univ Sci & Technol Dept Math & Stat Changsha Peoples R China Hunan Normal Univ Coll Life Sci Changsha Peoples R China

The support vector machine (SVM) is a powerful tool for pattern classification thanks to its outstanding efficiency. However, when encountering extensive classification tasks, the considerable computational complexity may present a substantial barrier. To reduce computational complexity, the novel ramp fraction loss SVM model called Lr f-SVM is introduced. The aim of this model is to simultaneously achieve sparsity and robustness. Utilizing our proposed proximal stationary point, we develop a novel optimality theory to the nonsmooth and nonconvex Lr f-SVM. Drawing upon this innovative theory, a novel efficient alternating direction method of multipliers (ADMM) incorporating a working set with low computational complexity will be introduced for handing Lr f-SVM. Moreover, our algorithm has shown that it can achieve global convergence. Our algorithm has been shown to be highly efficient through numerical experiments, surpassing nine other top solvers regarding number of support vectors, speed of computation, accuracy of classification and robust to outliers. For example, for addressing the real dataset over 107samples, our algorithm can finish the classification in just 18.67 s, a notable enhancement in comparison to other algorithms that need at least 605.3 s.

关键词： Ramp fraction loss SVM low computational complexity Fast algorithm Sparsity and robustness Large-scale classification

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low computational complexity Digital Predistortion Based on Convolutional Neural Network for Wideband Power Amplifiers

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2022年第3期69卷 1702-1706页

作者： Liu, Zhijun Hu, Xin Xu, Lexi Wang, Weidong Ghannouchi, Fadhel M. Beijing Univ Posts & Telecommun Sch Elect Engn Beijing 100876 Peoples R China China United Network Commun Corp Res Inst Beijing 100048 Peoples R China Univ Calgary Schulish Sch Engn Dept Elect & Comp Engn Intelligent RF Radio Lab Calgary AB T2N 1N4 Canada

The convolutional neural network (CNN) based power amplifier (PA) model has been proven to reduce the model complexity significantly. However, due to the calculation mode of the convolutional structure, the application of the CNN-based predistortion model still faces the problem of high computational complexity. In this letter, we use one lightweight CNN to propose a modeling method of the predistorter with low computational complexity for the wideband PA. This method first decomposes the traditional two-dimensional convolution kernels into two kinds of one-dimensional convolution kernels, to create the predesigned filter layer. These two kinds of convolution kernels are used to successively construct the nonlinear terms and the cross basis function terms required by the digital predistortion (DPD) model, respectively. Then, the unnecessary connections of the fully connected structure are removed using the pruning method based on amplitudes, to further reduce the complexity. Experimental results based on 100 MHz Doherty PA show that this predistortion model can significantly reduce the computational complexity, while ensuring that the linearization effects do not deteriorate.

关键词： Convolution computational modeling Predistortion Kernel Training Convolutional neural networks computational complexity Lightweight convolutional neural network (CNN) digital predistortion (DPD) wideband power amplifiers (PAs) low computational complexity linearization

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low computational complexity Algorithm for Hand Gesture Recognition using mmWave RADAR

Low Computational Complexity Algorithm for Hand Gesture Reco...

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International Symposium on Wireless Communication Systems (ISWCS)

作者： Zhao, Yanhua Sark, Vladica Krstic, Milos Grass, Eckhard IHP Leibniz Inst Innovat Mikroelekt Frankfurt Oder Germany Univ Potsdam Potsdam Germany Humboldt Univ Inst Comp Sci Berlin Germany

ISBN: (数字)9781665455442

ISBN: (纸本)9781665455442

Radio detection and ranging (RADAR) technology has attracted a lot of attention recently, especially for hand gesture recognition. Contactless hand gesture recognition can be applied in many areas, such as in-car entertainment systems and clean room operations. In this work, a computationally efficient and fast hand gesture feature extraction approach based on frequency-modulated continuous-wave (FMCW) RADAR is proposed, which is highly beneficial for real-time applications. Unlike conventional image recognition, the features of the hand gesture are extracted directly in an efficient manner. Our approach adopts 2-dimensional Fast Fourier Transform (FFT) to form a Range-Doppler matrix, and background modelling to remove clutter. Furthermore, we use best bin selection to locate the target in the Range-Doppler matrix in order to obtain both range and velocity of targets. Fourier beam steering is employed to obtain the angle of targets. Four classifiers are trained to perform hand gesture recognition. Cross-validation is used to evaluate their performance. Experimental results indicate that the features extracted by our approach can be fed directly into the classifiers for recognition which leads to an average recognition accuracy of 98.74% across all classifiers. Compared to image based recognition, the additional feature extraction process can be skipped, saving significant processing time. Our approach could be useful in many areas such as incar entertainment systems, smart homes and others.

关键词： FMCW RADAR mmWave Gesture Sensing low computational complexity

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Blind single image super resolution with low computational complexity

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MULTIMEDIA TOOLS AND APPLICATIONS 2017年第5期76卷 7235-7249页

作者： Kim, Won-Hee Lee, Jong-Seok Yonsei Univ Yonsei Inst Convergence Technol 85 Songdogwahak Ro Incheon South Korea Yonsei Univ Sch Integrated Technol 85 Songdogwahak Ro Incheon South Korea

This paper proposes a single image super resolution algorithm with the aim of satisfying three desirable characteristics, namely, high quality of the produced images, adaptability to image contents and unknown blurring conditions used to generate given input images, and low computational complexity. After the given input image is upscaled using a conventional reconstruction operator, the missing high frequency components estimated from lower resolution versions of the input image are added for improved quality and, moreover, the amount of the high frequency components to be added is adaptively determined. No computationally intensive operation is involved in the whole process, which makes the method computationally cheap. Experimental results show that the proposed method yields good subjective and objective image quality consistently across different blurring conditions and contents, and operates fast in comparison to existing state-of-the-art algorithms. In addition, it is also demonstrated that the proposed method can be used in combination with the existing algorithms in order to improve further their performance in terms of image quality.

关键词： Single image super resolution Adaptive weighting Image quality low computational complexity

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A Novel low computational complexity Power Assignment Method for Non-orthogonal Multiple Access Systems

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2014年第1期E97A卷 57-68页

作者： Li, Anxin Harada, Atsushi Kayama, Hidetoshi DOCOMO Beijing Commun Labs Co Ltd Beijing 100190 Peoples R China

Multiple access (MA) technology is of most importance for beyond long term evolution (LTE) system. Non-orthogonal multiple access (NOMA) utilizing power domain and advanced receiver has been considered as a candidate MA technology recently. In this paper, power assignment method, which plays a key role in performance of NOMA, is investigated. The power assignment on the basis of maximizing geometric mean user throughput requires exhaustive search and thus has an unacceptable computational complexity for practical systems. To solve this problem, a novel power assignment method is proposed by exploiting tree search and characteristic of serial interference cancellation (SIC) receiver. The proposed method achieves the same performance as the exhaustive search while greatly reduces the computational complexity. On the basis of the proposed power assignment method, the performance of NOMA is investigated by link-level and system-level simulations in order to provide insight into suitability of using NOMA for future MA. Simulation results verify effectiveness of the proposed power assignment method and show NOMA is a very promising MA technology for beyond LTE system.

关键词： non-orthogonal multiple access power assignment low computational complexity tree search beyond LTE system

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The Input-Mapping-Based Online Learning Sliding Mode Control Strategy With low computational complexity

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2024年 22卷 7670-7678页

作者： Yu, Yaru Ma, Aoyun Li, Dewei Xi, Yugeng Gao, Furong Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Key Lab Syst Control & Informat Proc Minist Educ China Shanghai 200240 Peoples R China Hong Kong Univ Sci & Technol Dept Chem & Biol Engn Hong Kong Peoples R China

The data-driven sliding mode control (SMC) method proves to be highly effective in addressing uncertainties and enhancing system performance. In our previous work, we implemented a co-design approach based on an input-mapping data-driven technique, which effectively improves the convergence rate through historical data compensation. However, this approach increases computational complexity in multi-input and multi-output (MIMO) systems due to the dependency of the number of online optimization variables on system dimensions. To improve applicability, this paper introduces a novel input-mapping-based online learning SMC strategy with low computational complexity. First, a new sliding mode surface is established through online convex combination of pre-designed offline surfaces. Then, an input-mapping-based online learning sliding mode control (IML-SMC) strategy is designed, utilizing a reaching law with adaptively adjusted convergence and switching coefficients to minimize chattering. The input-mapping technique employs the mapping relationship between historical input and output data for predicting future system dynamics. Accordingly, an optimization problem is formulated to learn from the past dynamics of the uncertain system online, thereby enhancing system performance. The optimization problem in this paper features fewer variables and is independent of system dimension. Additionally, the stability of the proposed method is theoretically validated, and the advantages are demonstrated through a MIMO system. Note to Practitioners-The design of control strategies that reduce the impact of mismatches between practical systems and models on system performance, while also ensuring applicability, is crucial. To address this issue, this paper proposes a low-complexity IML-SMC strategy. This strategy uses historical real input-output information and the mapping relationship with future dynamics to compensate for the impact of unknown dynamics and improve the system's conv

关键词： computational complexity Optimization Uncertainty Convergence Sliding mode control System performance Robustness MIMO communication computational modeling Switches Sliding mode control (SMC) input-mapping technique convex combined sliding mode surface low computational complexity

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A low computational complexity Scheme for Designing Linear Phase Sparse FIR Filters

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2022年第3期41卷 1550-1562页

作者： Li, Yi Zhao, Jiaxiang Xu, Wei Sun, Guiling Nankai Univ Coll Elect Informat & Opt Engn Tianjin Peoples R China Tianjin Polytech Univ Sch Elect & Informat Engn Tianjin Peoples R China

A low complexity scheme is developed to design the sparse linear phase FIR filters based on the improved iteratively re-weighted orthogonal matching pursuit(OMP) algorithm. The scheme employs the Frobenius norm to simplify searching for the desired sparse FIR filter at each iteration. Furthermore, a log function is introduced to enhance the weight updating process at each iteration. The simulation results demonstrate that our scheme can effectively generate the sparse linear phase FIR filters which satisfy the various given design specifications.

关键词： Sparse FIR filter Frobenius norm Linear phase low computational complexity Effective length

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A low computational complexity Frequency Estimation Method with High Precision of Sinusoid Based on DFT 4

A Low Computational Complexity Frequency Estimation Method w...

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4th International Conference on Information Science and Control Engineering (ICISCE)

作者： Xu, Chongjian Zhou, Lingyun Chen, Chang Zhang, Qingyuan Univ Sci & Technol China Chinese Acad Sci Key Lab Electromagnet Space Informat Hefei Anhui Peoples R China

ISBN: (纸本)9781538630136

In this paper, a new synthetic frequency estimator of sinusoid signal based on discrete Fourier transform (DFT) amplitudes is proposed. Compared with the existing methods, the proposed method has the advantages of low computational complexity and high precision. The method has two main stages. Firstly, N-point sampled data in the time domain DFT is performed and the coarse estimation is completed by searching the location of the spectrum line with maximum amplitude. Secondly, the synthetic fine estimation is performed by utilizing both the two samples values of Discrete-Time Fourier Transform (DTFT) of the original signal and the maximum amplitude spectrum line and its right or left neighbor. To verify the proposed method, simulation is conducted. The result shows that the root mean square error (RMSE) of frequency estimation of proposed synthetic method is close to the Cramer-Rao lower Bound, and it outperforms the Candan method. This method is also comparable to Fang method and RCTSL method with zero-padding when conducted under medium and high SNR condition. Moreover, without zero padding, the proposed method has much lower computational complexity than other known estimators with zero-padding.

关键词： signal processing frequency estimation sinusoid DFT low computational complexity

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AOA-constrained adaptive fault-tolerant control of hypersonic flight vehicles with low computational complexity 41

AOA-constrained adaptive fault-tolerant control of hypersoni...

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第41届中国控制会议

作者： Haochun Miao Yajun Li Gen Wang Jiang Chang Jinping Li Xi'an Modern Control Technology Research Institute

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,the longitudinal control problem of hypersonic flight vehicles(HFVs) with the angle of attack(AOA)constraint,external disturbances,unknown time-varying actuator fault and dead-zone is ***,by applying nonlinear state transformation technique,the original model is converted into a new pure-feedback form,and the AOA constraint can be guaranteed by ensuring the boundness of the transformed ***,a novel fault-tolerance fuzzy adaptive controller is *** logic systems are introduced to approximate the unknown nonlinear dynamics with only one learning parameter being updated online,which leads to a low computational ***,the unknown actuator dynamics including unknown time-varying actuator fault and dead-zone are well addressed by constructing a bound-estimation *** stability of the closed-loop system is proved via Lyapunov method,and the effectiveness of the proposed control scheme is demonstrated with numerical simulations.

关键词： Hypersonic flight vehicle(HFV) Angle of attack(AOA) constraint unknown time-varying faults dead-zones low computational complexity bound-estimation approach

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A foreground digital calibration algorithm for time-interleaved ADCs with low computational complexity

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MICROELECTRONICS JOURNAL 2023年 136卷

作者： Wang, Song Cheng, Xu Guo, Zi-Yu Han, Jun Fudan Univ State Key Lab ASIC & Syst Shanghai 200433 Peoples R China

In front of the offset, gain, timing, and bandwidth mismatch errors, time-interleaved analog-to-digital convert-ers (TIADCs) are usually calibrated to achieve satisfying performance. In this paper, we propose a new digital calibration approach for TIADCs, including the direction-distance search algorithm and multiplier-free gradient descent method. Compared to state-of-the-art multiplication-less techniques, this approach significantly reduces time complexity by minimizing search space dimension, subtracting the number of searches, and varying iteration step size. Notably, no multiplier is needed in the mismatch estimation, resulting in a much lower computational complexity than in previous work. For a 12-bit 4-channel TIADC, simulation results show that the signal-to-noise-and-distortion ratio is improved from 25 dB to 65 dB within the duration of 1600 samples. The proposed calibration circuit is synthesized targeting standard 28-nm technology, occupying the area of 0.014 mm2 and dissipating the power of 19 mW at 2.8 GHz clock frequency.

关键词： Time-interleaved ADC Digital calibration Optimization algorithm Gradient descent low computational complexity

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