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检索条件"主题词=filtering algorithms"

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Evaluation of Speech Enhancement algorithms for Hearing Aids

Evaluation of Speech Enhancement Algorithms for Hearing Aids

引用

North Karnataka Subsection Flagship International Conference (NKCon), IEEE

作者： Sunilkumar M. Hattaraki Shankarayya G. Kambalimath Lakshmi Khedagi Kavya Halemani Anjali Bhairagond Prjwal Hiremath Department of E&CE B.L.D.E.A’s V.P. Dr. P.G. Halakatti. College of Engineering and Technology Vijayapura India Visvesveraya Technological University Belagavi Karnataka India Department of E&CE Basaveshwar Engineering College Bagalkote Karnataka India

ISBN: (数字)9798350364569

ISBN: (纸本)9798350364576

This study evaluates the performance of speech enhancement algorithms aimed at improving speech quality, particularly in the context of hearing aids. Four algorithms, namely Non-Negative Matrix Factorization (NMF), Wiener filtering, Logarithmic Minimum Mean Square Error (LogMMSE), and Minimum Mean Square Error Short-Time Spectral Amplitude (MMSE-STSA), are applied to noisy speech recordings to reduce noise and enhance speech clarity. Evaluation metrics such as Signal-to-Noise Ratio (SNR), Perceptual Evaluation of Speech Quality (PESQ), and Short-Time Objective Intelligibility (STOI) are used to assess algorithm effectiveness. Results indicate that the NMF algorithm achieves the highest SNR (4.33796), demonstrating strong noise reduction capability. However, Wiener and LogMMSE algorithms exhibit the highest PESQ scores (1.61774), suggesting superior perceived speech quality. MMSE-STSA algorithm performs best in intelligibility with an STOI of 0.739275. These findings offer valuable insights into algorithm performance, crucial for optimizing speech enhancement in hearing aids to enhance speech intelligibility and quality. The study underscores the importance of considering multiple metrics when selecting suitable algorithms for hearing aid technology, providing a comprehensive understanding of their effectiveness in real-world applications. Such insights contribute to the development of more effective speech enhancement solutions for hearing aid users.

关键词： Wiener filters Mean square error methods Speech enhancement filtering algorithms Hearing aids Recording Noise measurement Signal to noise ratio

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Research on Autonomous Detection algorithms for Spoofed Interference in Civil Aircraft Airborne Navigation Systems

Research on Autonomous Detection Algorithms for Spoofed Inte...

引用

Power, Electrical Engineering, Electronics and Control (PEEEC), International Conference on

作者： Jia Chen Commercial Aircraft Corporation of China Ltd Beijing Aeronautical Science &Technology Research Institute of COMAC Beijing China

ISBN: (数字)9798350378917

ISBN: (纸本)9798350378924

With the wide application of civil aircraft on-board navigation system, the demand for its safety and stability is increasing. In this paper, the aircraft navigation state data is acquired by GNSS and INS sensors, and the navigation state model is constructed. Through Kalman filtering algorithm, any abnormal or inconsistent navigation state is detected to monitor the real-time performance of the navigation system. When potential deceptive interference is detected, the algorithm is able to take appropriate decisions autonomously, such as switching to an alternate navigation system, sending warning notifications to the flight crew, and so on. In the simulated spoofed interference scenario, the algorithm successfully detected more than 95% of the interference events with an average response time of less than 5 seconds. When the on-board GNSS spoofing causes a position deviation of 250 m or more, the designed algorithm is able to realize a more accurate acquisition of the spoofing duration. The reliability and effectiveness of the proposed algorithm in spoofed jamming scenarios are verified, and the anti-jamming capability of the civil aircraft airborne navigation system is improved.

关键词： Global navigation satellite system Accuracy Interference filtering algorithms Aerospace electronics Aircraft navigation Aircraft manufacture Time factors Aircraft Detection algorithms

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A Kind of SLAM Algorithm Based on Strong Tracking Cubature Kalman Filter

A Kind of SLAM Algorithm Based on Strong Tracking Cubature K...

引用

Advanced algorithms and Control Engineering (ICAACE), International Conference on

作者： Guangsong Yang Yangfan Cui Yujun Lin Longxing Liu Bing Li School of Ocean Information Engineering Jimei University Xiamen Fujian China

ISBN: (数字)9798350361445

ISBN: (纸本)9798350361452

Simultaneous Localization and Mapping (SLAM) of mobile robots should satisfy some requirements for calculation accuracy and speed. When observation noise is time-varying and mixed, the filter accuracy will decrease or even divergence, which leads to more position errors or even failure of the mobile robot. To solve the problem, the Strong Tracking Cubature Kalman SLAM algorithm (CKFST-SLAM) is improved. Firstly, the noise estimator is introduced to estimate the noise unbiasedly, and the statistical characteristics of the noise are estimated and corrected in real time. Secondly, the diagonalization of the matrix (DM) is used to replace the Cholesky decomposition in the update phase of the mobile robot position in the algorithm. This algorithm enhances the robustness of the inaccurate statistical characteristics of noise effectively and improves the filter accuracy and stability. The simulation experiment results show that compared with the CKFST-SLAM, the Root Mean Square Error (RMSE) of the algorithm proposed in this paper is reduced by 43.8% and 34.8% under two scenarios with different observation noise.

关键词： Simultaneous localization and mapping Uncertainty Noise filtering algorithms Stability analysis Robustness Mobile robots

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Matrix Spectral Factorization for Alpert Multiwavelet Filter Bank

Matrix Spectral Factorization for Alpert Multiwavelet Filter...

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National Conference with International Participation (TELECOM)

作者： Vasil Kolev Todor Cooklev Bulgarian Academy of Sciences Institute of Information and Communication Technologies Sofia Bulgaria Department of Electrical and Computer Engineering Purdue University Fort Wayne Indiana USA

ISBN: (数字)9798350355000

ISBN: (纸本)9798350355017

Multiwavelets can be orthogonal, symmetric, smooth, and with short support, all at the same time. However, the design of multifilters with these properties remains a challenging problem. Obtaining multifilters by using matrix spectral factorization (MSF) is still quite unknown in the signal processing community. There are a number of numerical approaches to MSF, but they usually cannot handle the case when the determinant of the matrix product filter has zeros on the unit circle (i.e. singularity), which is precisely of greatest interest in the construction of multiwavelets. We describe a novel design of Alpert's multiwavelet filter using Bauer's method for MSF of a product multifilter. We apply the proposed multifilter for image denoising of gray images and compare with the orthogonal GHM and CL multifilters.

关键词： Symmetric matrices Filter banks Signal processing algorithms filtering algorithms Signal processing Encoding Telecommunications Image denoising

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Improving the performance of Block Sparse Set-Membership PNLMS Algorithm using L1 norm

Improving the performance of Block Sparse Set-Membership PNL...

引用

IEEE Calcutta Conference (CALCON)

作者： Nilkamal Bhunia Bijit Kumar Das Dept. of Electronics and Communication Engineering Dr. B. C. Roy Engineering College Durgapur India Dept. of Electronics and Communication Engineering Indian Institute of Information Technology Guwahati Guwahati India

ISBN: (数字)9798331516666

ISBN: (纸本)9798331516673

In this paper, an improved block-sparse set-membership proportionate normalized least mean square algorithm (PNLMS) algorithm is introduced. The algorithm, termed as the $L_{1}$-SMBPNLMS, is designed by adding a penalty of the $L_{1}$ norm of filter weight-tap vector into the cost function of the set membership block PNLMS (SMBPNLMS) algorithm. Simulation results show that the proposed $L_{1}$-SMBPNLMS algorithm converges very fast, and attains a very low steady state mean square deviation with respect to other contemporary and related algorithms.

关键词： Simulation Clustering algorithms filtering algorithms Cost function Vectors Steady-state

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Performance Analysis of Non-Local Means Denoising on Medical Images and the Impact of Filter Parameter Variation

Performance Analysis of Non-Local Means Denoising on Medical...

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International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)

作者： Preena Prasad J Anitha Blesson Biji Department of Electronics and Communication Engineering Karunya Institute of Technology and Sciences Coimbatore & SAINTGITS College of Engineering Kottayam India Department of Electronics and Communication Engineering Karunya Institute of Technology and Sciences Coimbatore India Department of Electronics and Communication Engineering SAINTGITS College of Engineering Kottayam India

ISBN: (数字)9798350350845

ISBN: (纸本)9798350350852

In medical imaging, diagnostic accuracy depends on clear images, which are frequently damaged by noise. To address this researchers have developed a number of noise reduction techniques, each with unique benefits and limitations. The effectiveness of NLM (Non-Local Means) denoising in medical images at various noise levels is comprehensively examined in this work. The goal is to understand how key parameters patch size, window size, and smoothing parameter (h) interact under different noise conditions. MSE (Mean Square Error), PSNR (Peak Signal-to-Noise Ratio), and SSIM (Structural Similarity Index) metrics are applied in performance evaluation to provide quantitative insights into the efficiency of denoising and structural preservation. Experiments are conducted using a diverse dataset that includes MRI (Magnetic Resonance Images) and CT (Computed Tomography). Throughout the study, consistent patch sizes of 3 and 5, along with a window size of 11 and 15, are used to explore the role of the smoothing parameter for different noise levels and assess denoising efficacy at various noise intensities. This study contributes to understanding the potential of NLM denoising in improving image quality under varying noise situations, emphasizing the significance of deliberate filter parameter selection over random choices for improved denoising in both objective and subjective approaches.

关键词： Wireless communication Smoothing methods PSNR Computed tomography Noise reduction Signal processing algorithms filtering algorithms

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An Efficient Implementation of the Fast Product Multi-Sensor Labeled Multi-Bernoulli Filter

An Efficient Implementation of the Fast Product Multi-Sensor...

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International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)

作者： Charlotte Hermann Alexander Scheible Michael Buchholz Klaus Dietmayer Institute of Measurement Control and Microtechnology Ulm University Ulm Germany

ISBN: (数字)9798350368031

ISBN: (纸本)9798350368048

In Random Finite Set based multi-sensor multi-object tracking, the NP-hard measurement-to-track assignment problem is a key challenge. One approach to address this challenge involves executing computationally simpler single-sensor updates based on a common prediction, followed by the fusion of these updates. This strategy is used by the already proposed Fast Product Multi-Sensor Labeled Multi-Bernoulli filter, which still poses computational challenges in its existing formulation. This paper introduces an efficient implementation of the Fast Product Multi-Sensor Labeled Multi-Bernoulli filter by improving the efficiency of the individual single-sensor updates and the fusion of the resulting single-sensor posterior densities. Two different approaches are presented for each part, including the new GeneralizedKBestSelection algorithm, which solves a $k$ shortest path problem on highly structured graphs. Our approach is evaluated on simulations, and the results are compared with an Iterated Corrector implementation of the Labeled Multi-Bernoulli filter using comparable simplifications.

关键词： Shortest path problem Computational modeling filtering algorithms Approximation algorithms Computational efficiency Intelligent systems Computational complexity

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MSCKF-DVIO: Multi-State Constraint Kalman Filter based RGB-D Visual-Inertial Odometry with Spline Interpolation and Nonholonomic Constraint

MSCKF-DVIO: Multi-State Constraint Kalman Filter based RGB-D...

引用

International Conference on Ubiquitous Robots (UR)

作者： Kwangyik Jung Jaebong Song Samwoo Seong Hyun Myung Department of Autonomous Driving Software Development Twinny Yuseong-gu Republic of Korea Urban Robotics Lab School of Electrical Engineering Korea Advanced Institute of Science and Technology Republic of Korea

ISBN: (数字)9798350361070

ISBN: (纸本)9798350361087

This study presents MSCKF-DVIO (Multi-State Constraint Kalman Filter - Depth-aided Visual Inertial Odom-etry) as an innovative approach to address the limitations of existing methods. MSCKF-DVIO leverages RGB-D images and low-cost IMU measurements to enhance the accuracy and efficiency of visual-inertial odometry systems. The proposed framework jointly optimizes RGB-D images and low-cost IMU measurements, enabling robust and precise state estimation. By reducing the number of state variables compared to the existing MSCKF-VIO, the efficiency of state augmentation and covariance computations is significantly enhanced. Notably, the prediction of the future state is achieved through the interpolation of past keyframe viewpoint poses from the image and short-time IMU integration. The proposed MSCKF-DVIO improves the accuracy of estimation by applying nonholonomic constraints (NHCs) of a differential-wheeled mobile robot and utilizing the zero velocity update (ZUPT) based on stationary state determination. The efficacy of MSCKF -DVIO is evaluated through the Absolute Pose Error (APE) using 3D LiDAR-based localization as the ground truth. The evaluation includes pose estimation outcomes and performance evaluations in comparison to other algorithms. The results demonstrate significant promise of MSCKF-DVIO for improving the performance and reliability of visual-inertial odometry systems.

关键词： Interpolation Visualization Accuracy Stationary state filtering algorithms Information filters Real-time systems

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Odometry Estimation by Fusing Multiple Radar Sensors and an Inertial Measurement Unit

Odometry Estimation by Fusing Multiple Radar Sensors and an ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Tim Brühl Tim Dieter Eberhardt Robin Schwager Lukas Ewecker Tin Stribor Sohn Sören Hohmann Dept. of Highly Automated Driving Systems Dr. Ing. h.c. F. Porsche AG Weissach Germany Institute of Control Systems Karlsruhe Institute of Technology Germany Hochschule für Technik und Wirtschaft Berlin Germany

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper presents a framework for odometry estimation in automotive application using six asynchronously operating millimeter wave radar sensors and a combination of gyroscope and accelerometer. Two different motion models are combined to estimate motion with three degrees of freedom. For this purpose, we propose a novel three-part radar filtering method for outlier detection: By analyzing uncertainties and system limits, sensor-specific outliers are detected and removed in the first filter. We introduce knowledge about the previous motion state by a status-quo-ante filter and hereby identify further false positive raw targets in the current measure which are not accessible from the previous state. Moreover, we suggest employing a downstream, resampling-based algorithm for additional outlier detection. Based on the filtered data, radar motion state estimation is performed by use of curve fitting methods. To fuse the radar odometry estimation with the acceleration and yaw rate measurements handling non-linearities, an Unscented Kalman Filter is used. The developed framework is evaluated with reference data in various scenarios. The results demonstrate that it accurately and robustly determines motion and position states even in radar-challenging scenes, such as environments with few radar targets or with heavy metal structures. Our method keeps up with common approaches such as wheel speed sensor odometry while outperforming it in terms of drift-impairment.

关键词： Accelerometers Uncertainty Radar measurements Wheels Radar filtering algorithms Millimeter wave radar

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Using Generative Adversarial Networks for Design of Passive Microstrip Filters

Using Generative Adversarial Networks for Design of Passive ...

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International Conference on Microwave and Millimeter Wave Technology Proceedings

作者： Chen Chen Nie Qing Chen Zhong Fang Ren Hai Peng Wang Yun Bo Li Research Center of Applied Electromagnetics Nanjing University of Information Science & Technology Nanjing China State Key Laboratory of Millimeter Waves Southeast University Nanjing China Nanjing Xinda Institute of Safety and Emergency Management Nanjing China

ISBN: (数字)9798350389968

ISBN: (纸本)9798350389975

For the microstrip filter design, traditional iterative optimization methods are time-consuming and resource-intensive. In this paper, a passive microstrip filter inverse design method based on generative adversarial networks (GAN) is presented. It can automatically design passive filters under given single-band and dual-band magnitude responses. The overall framework includes a GAN-based graphic generator, a convolution neural network (CNN)-based electromagnetic response predictor, and a genetic algorithm optimizer. By constructing a hybrid model of the filter unit structure and electromagnetic response, a solution that meets the requirements of the target frequency response is finally inversely designed. The inverse-designed filters are then verified by simulations and comparisons with the targets. The proposed method enables the one-time solution of the patch structure and parameters of microstrip filters, with the advantages of automation, fast speed, and low computational resource consumption.

关键词： Microstrip filters Automation Passive filters Scalability Dual band filtering algorithms Generative adversarial networks

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