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arXiv 2025年

作者： Basu, Amlan Chaudhari, Pranav Di Caterina, Gaetano Neuromorphic Sensor Signal Processing Lab Centre for Image and Signal Processing Electrical and Electronic Engineering Department University of Strathclyde Glasgow United Kingdom

Audio classification is paramount in a variety of applications including surveillance, healthcare monitoring, and environmental analysis. Traditional methods frequently depend on intricate signal processing algorithms and manually crafted features, which may fall short in fully capturing the complexities of audio patterns. Neuromorphic computing, inspired by the architecture and functioning of the human brain, presents a promising alternative for audio classification tasks. This survey provides an exhaustive examination of the current state-of-the-art in neuromorphic-based audio classification. It delves into the crucial components of neuromorphic systems, such as Spiking Neural Networks (SNNs), memristors, and neuromorphic hardware platforms, highlighting their advantages in audio classification. Furthermore, the survey explores various methodologies and strategies employed in neuromorphic audio classification, including event-based processing, spike-based learning, and bio-inspired feature extraction. It examines how these approaches address the limitations of traditional audio classification methods, particularly in terms of energy efficiency, real-time processing, and robustness to environmental noise. Additionally, the paper conducts a comparative analysis of different neuromorphic audio classification models and benchmarks, evaluating their performance metrics, computational efficiency, and scalability. By providing a comprehensive guide for researchers, engineers and practitioners, this survey aims to stimulate further innovation and advancements in the evolving field of neuromorphic audio classification. © 2025, CC BY.

关键词： Benchmarking

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COMMON PITFALLS IN THE APPLICATION OF STATIONARY PROCESS THEORY TO TIME-SAMPLED AND MODULATED signalS

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IEEE TRANSACTIONS ON COMMUNICATIONS 1987年第5期35卷 529-534页

作者： GARDNER, WA Signal and Image Processing Lab Signal and Image Processing Lab Department of Electrical and Computer Engineering University of California Davis CA USA

The common practice of applying the theory of stationary stochastic processes to a cyclostationary process by introducing random phase(s) into the probabilistic model in order to stationarize the process can lead to erroneous results, such as incorrect formulas for power spectral density. This is illustrated by showing that commonly used formulas for signals that have undergone frequency conversion or time sampling can be incorrect. The source of error is shown to be inappropriate phase-randomization procedures. The correct procedure is described, and corrected formulas are given. The problem is further illustrated by showing that commonly used resolution and reliability (mean and variance) formulas for spectrum analyzers must be corrected for cyclostationary signals. It is explained that all corrections to formulas reflect the effects of spectral correlation. These effects are inappropriately averaged out by inappropriate phase-randomization procedures. It is further explained that these inappropriate procedures destroy the important property of ergodicity of the probabilistic model.

关键词： signal processing Stochastic processes Phase modulation Frequency conversion signal sampling Spectral analysis Pulse modulation signal resolution Analytical models

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Autonomous Path Planning via Sand Cat Swarm Optimization With Multi-Strategy Mechanism for Unmanned Aerial Vehicles in Dynamic Environment

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IEEE Internet of Things Journal 2025年

作者： Deng, Wu Feng, Jiayi Zhao, Huimin Civil Aviation University of China College of Electronic Information and Automation Tianjin300300 China Civil Aviation University of China Tianjin Key Lab Intelligent Signal and Image Processing Tianjin300300 China State Key Laboratory of Rail Transit Vehicle System of Southwest Jiaotong University Chengdu610031 China

Unmanned Aerial Vehicles (UAVs) face critical challenges in path planning in dynamic environment. Sand Cat Swarm Optimization (SCSO) algorithm has demonstrated promise in addressing complex optimization challenges. However, SCSO is limited by slow convergence, susceptibility to local optima, and insufficient adaptability. To overcome these shortcomings, an enhanced SCSO with the spiral search, Livy flight, tent chaotic mapping, and adaptive sparrow alert mechanism, namely TSLS-SCSO is developed to propose an autonomous path planning method for UAVs in dynamic environment. In TSLS-SCSO, a new population initialization strategy with tent chaotic mapping is designed to achieve a large dynamic range and coverage capability. Then a new spiral search strategy is designed to broaden the search range in the search phase. And a new Livy flight strategy is employed to enrich the diversity of population in the attacking prey phase. A new sparrow alert mechanism with integrating the sand cat group with the sparrow alert is designed to obtain faster convergence speed and accuracy. The experiment results on CEC 2017 and CEC 2022 show that the TSLS-SCSO obtains higher accuracy and more stable solutions and exhibits better competitiveness. Furthermore, the proposed UAV path planning method successfully found effective paths with an obstacle avoidance effectiveness of 95.5%. The obtained results validate the effectiveness and competitiveness of TSLS-SCSO in UAV path planning in the dynamic environment. © 2014 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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NEW TECHNIQUE FOR HIGH-SPEED PIPELINED IIR RNS DIGITAL FILTERS.

NEW TECHNIQUE FOR HIGH-SPEED PIPELINED IIR RNS DIGITAL FILTE...

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Proceedings - 1984 IEEE International Symposium on Circuits and Systems.

作者： Soderstrand, Michael A. Sinha, Bhaskar Univ of California Davis Signal & Image Processing Lab Davis CA USA Univ of California Davis Signal & Image Processing Lab Davis CA USA

The well-known advantages of pipelining as applied to Finite Impulse Response (FIR) Residue Number System (RNS) arithmetic digital filters is extended to the important area of Infinite Impulse Response (IIR) digital filters through a new technique based on augmentation of the IIR transfer function. Through this technique, pipelined IIR filters based on RNS Read-Only-Memory (ROM) table look-up techniques can be designed which offer throughput rates equal to the table look-up time of the ROMs. This high-speed realization can be achieved even though the recursive filter algorithm requires multiple delays in realizing the output of the filter. For the example of a typical second-order IIR filter, the pipelined structure represents a five-fold increase in speed over standard techniques. Higher order realizations will yield proportionately higher speed improvements. This paper discusses the basic technique, stability considerations, and hardware realizations.

关键词： ELECTRIC FILTERS, DIGITAL

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MODEL FOR GRAPHICS INTERFACE TOOL DEVELOPMENT.

MODEL FOR GRAPHICS INTERFACE TOOL DEVELOPMENT.

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Proceedings - Graphics Interface '85.

作者： Joy, Kenneth I. Univ of California Davis Signal & Image Processing Lab Davis CA USA Univ of California Davis Signal & Image Processing Lab Davis CA USA

A Problem Solving Environment (PSE) is an integrated system that supports the solution of a given problem, or a set of problems. Paramount in the development of such environments is the design, specification and integration of user interface tools that communicate between the system and the user. Typically these interactions are object oriented and involve the interaction with tool parameters, which in many applications (CAD/CAM, Imaging Systems, image processing), are represented by graphical data. This paper describes a user-interface tool development system in which both textual and graphical display, and interaction techniques are integrated under a single model. This allows the user to interact with tool parameters in either graphical or textual modes, and to have the parameters displayed in the manner most relevant to the problem set. Examples are given of the systems use in two different problem sets.

关键词： COMPUTER GRAPHICS

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RECURSIVE SYNTHESIS OF LINEAR TIME-VARIANT DIGITAL FILTER VIA CHEBYSHEV APPROXIMATION.

RECURSIVE SYNTHESIS OF LINEAR TIME-VARIANT DIGITAL FILTER VI...

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Proceedings - 1984 IEEE International Symposium on Circuits and Systems.

作者： Park, Sunghan Aggarwal, J.K. Univ of Texas at Austin Lab for Image & Signal Processing Austin TX USA Univ of Texas at Austin Lab for Image & Signal Processing Austin TX USA

The paper investigates problems associated with the realization of a generalized transfer function as a recursive difference equation with time-variant coefficients. We develop a relationship between a generalized transfer function and a time-variant difference equation. Procedures for determining a time-variant difference equation from a given generalized transfer function are then developed. For a generalized transfer function with time-variant coefficients in its denominator, a 'best' approximate realization is numerically determined based on the Chebyshev norm to minimize the residual vector.

关键词： ELECTRIC FILTERS, DIGITAL

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Revolutionary entrapment model of uniformly distributed swarm robots in morphogenetic formation

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Defence Technology（防务技术） 2024年第1期31卷 496-509页

作者： Chen Wang Zhaohui Shi Minqiang Gu Weicheng Luo Xiaomin Zhu Zhun Fan Shantou University ShantouGuangdongChina National University of Defense Technology ChangshaChina Key Lab of Digital Signal and Image Processing of Guangdong Province China

This study proposes a method for uniformly revolving swarm robots to entrap multiple targets,which is based on a gene regulatory network,an adaptive decision mechanism,and an improved *** the gene regulatory network method,the robots can generate entrapping patterns according to the environmental input,including the positions of the targets and ***,an adaptive decision mechanism is proposed,allowing each robot to choose the most well-adapted capture point on the pattern,based on its *** robots employ an improved Vicsek-model to maneuver to the planned capture point smoothly,without colliding with other robots or *** proposed decision mechanism,combined with the improved Vicsek-model,can form a uniform entrapment shape and create a revolving effect around targets while entrapping *** study also enables swarm robots,with an adaptive pattern formation,to entrap multiple targets in complex *** robots can be deployed in the military field of unmanned aerial vehicles’(UAVs)entrapping multiple *** experiments demonstrate the feasibility and superiority of the proposed gene regulatory network method.

关键词： Swarm intelligence Revolutionary entrapment Flocking Robots Gene regulatory network Vicsek-model Entrapping multiple targets

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signal processing for sound synthesis:: Computer-generated sounds and music for all

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IEEE signal processing MAGAZINE 2007年第2期24卷 8-+页

作者： Valimaki, Vesa Rabenstein, Rudolf Rocchesso, Davide Serra, Xavier Smith, Julius O. Key Lab of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi'an China Key Lab of Radar Signal Processing Xidian University Xi'an China

Almost everybody uses sound synthesis in their daily lives, although many may not know it.

关键词： Editors signal processing Music Synthesis of Sound

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Adaptive image compression using sparse dictionaries

Adaptive image compression using sparse dictionaries

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2012 19th International Conference on Systems, signals and image processing, IWSSIP 2012

作者： Horev, Inbal Bryt, Ori Rubinstein, Ron Signal and Image Processing Lab. Department of Electrical Engineering Technion Haifa Israel Geometric Image Processing Lab. Department of Computer Science Technion Haifa Israel

ISBN: (纸本)9783200023284

Transform coding is a widely used image compression technique, where entropy reduction can be achieved by decomposing the image over a dictionary which provides compaction. Existing algorithms, such as JPEG and JPEG2000, utilize fixed dictionaries which are shared by the encoder and decoder. Recently, works utilizing content-specific dictionaries show promising results by focusing on specific classes of images and using highly specialized dictionaries. However, such approaches lose the ability to compress arbitrary images. In this paper we propose an input-adaptive compression approach, which encodes each input image over a dictionary specifically trained for it. The scheme is based on the sparse dictionary structure, whose compact representation allows relatively low-cost transmission of the dictionary along with the compressed data. In this way, the process achieves both adaptivity and generality. Our results show that although this method involves transmitting the dictionary, it remains competitive with the JPEG and JPEG2000 algorithms. © 2012 Institute of Telecommunica.

关键词： image compression

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A Regularized Super Resolution Algorithm for Generalized Gaussian Noise

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Journal of Donghua University(English Edition) 2010年第1期27卷 25-35页

作者：陈文方向忠刘立峰蒋伟丁大为乔艳涛 Institute of Image Communication and Information Processing Shanghai Jiaotong University Computer and Information Department Shanghai University of Electric Power Key Lab oratory of Intelligent Computing & Signal Processing Ministry of EducationAnhui University

In this paper,an iterative regularized super resolution (SR) algorithm considering non-Gaussian noise is *** on the assumption of a generalized Gaussian distribution for the contaminating noise,an lp norm is adopted to measure the data fidelity term in the cost *** the meantime,a regularization functional defined in terms of the desired high resolution (HR) image is employed,which allows for the simultaneous determination of its value and the partly reconstructed image at each iteration *** convergence is thoroughly *** results show the effectiveness of the proposed algorithm as well as its superiority to conventional SR methods.

关键词： super resolution generalized p-Gaussian distribution regularization parameter

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