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TOWArdS AN INTELLIGENT PROBLEM-SOLVING ENVIRONMENT FOR signal-processing

MATHEMATICS AND COMPUTERS IN SIMULATION 1994年第4-6期36卷 347-3259页

作者： SEKHAR, C MOISAN, S THONNAT, M Action ORION INRIA Sophia-Antipolis 2004 Route des Lucioles BP-93 06902 Sophia-Antipolis Cedex France

Modern signal processing methods are typically quite complex, and a great deal of expertise is needed in selecting and using appropriate methods for an application. Since most users have little signal processing experience, the expertise of the signal processing specialist needs to be made more accessible to them. This can be done by means of knowledge-based systems developed using dedicated AI tools for signal processing, as proposed in this paper. We first discuss the types of knowledge and reasoning involved in SP problem-solving, and based on this, we propose an AI architecture which facilitates the expression of knowledge at the level of the SP specialist. SP methods are represented as operators, and grouped according to the SP goals they perform. processing is initiated by means of requests, which ask for a particular goal to be affected on a given data set. Two types of reasoning, planning and supervision, are required for the processing, and mechanisms for them are provided. The paper describes how a knowledge based system can be built using the proposed architecture, and how a given SP problem is solved by the KBS.

关键词： signal processing (SP) PROBLEM SOLVING KNOWLEDGE-BASED SYSTEMS (KBS) ARTIFICIAL INTELLIGENCE (AI)

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Towards unique performance using FPGAs in modern communication, data processing and sensor systems 3

Towards unique performance using FPGAs in modern communicati...

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3rd international conference on signal processing and Integrated Networks (SPIN)

作者： Voss, Sven-Hendrik Beuth Univ Appl Sci Comp Architecture & Digital Technol Luxemburger Str 10 D-13353 Berlin Germany

ISBN: (纸本)9781467391979

Modern innovative applications like machine-to-machine (M2M) communication, multi-gigabit data networks, extensive sensor networks or data acquisition and big data analytics require an enormous amount of processing power and bandwidth. The traditional approach to deploy a processing and transmission infrastructure by cascading multicore CPUs, using offload engines and GPU cores is usually expensive and not always practical, thus building an obstacle in front of creative and innovative applications. The use of Field Programmable Gate Arrays (FPGAs) in combination with a sophisticated design methodology has proven to overcome many of the usual obstacles. This paper gives an overview of innovative approaches in digital hardware design. The described approaches will be reflected by specific design examples of challenging applications.

关键词： Program processors

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A Comparison of Different signal processing Techniques for Upper Limb Muscle Activity Onset Detection using Surface Electromyography 3

A Comparison of Different Signal Processing Techniques for U...

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3rd international conference on Artificial Intelligence and signal processing, AISP 2023

作者： Koppolu, Pratap Kumar Chemmangat, Krishnan NIT Karnataka Surathkal Electrical & Electronics Engineering Department Mangalore575025 India

ISBN: (纸本)9798350320749

This work presents the use of real-time experimental Surface Electromyography (sEMG) signals to determine muscle activity of upper limb by detecting the exact onset and offset timings. Various muscle activity detection methods were evaluated, such as Sample Entropy (SEn), Permutation Entropy (PEn), Amplitude Aware Permutation Entropy (AAPEn), and Integrated Profile (IP). The performance of these methods was compared, and it was found that IP detects muscle activity quickly and requires less computation for real-time implementation as compared to other methods. © 2023 IEEE.

关键词： Muscle

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signal processing and Transmission in GIS Flashover Fault Location System 3

Signal Processing and Transmission in GIS Flashover Fault Lo...

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2017 3rd IEEE international conference on Control Science and Systems Engineering (ICCSSE)

作者： Shuang Xie Jialin Zhu School of Automation Beijing Information Science and Technology University

ISBN: (纸本)9781538604854

This paper introduces the detection principle of Gas-Insulated Switchgear(GIS) ultrasonic testing method for the fault location of flashover. We designed the GIS flashover fault location monitoring system, which solved the problem of low precision and time-consuming for the detection of GIS. We designed the hardware and software of the monitoring system. We use the three op amp differential amplifier circuit in front processing circuit of the hardware part to suppress the common mode signal in the signals. When the signal is processed by software, the method of wavelet soft and hard threshold is designed to remove the noise in the signal and improve the signal to noise ratio. We achieve the task of wireless data transmission through the Zig Bee2007 Proprotocol stack. Experimental platform is built to verify the reliability of the GIS flashover fault location system, which can improve the positioning accuracy and fault location, and has the advantages of low cost, portability and so on.

关键词： GIS flashover fault location three op amp differential circuit wavelet denoising ZigBee protocol

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MOISTURE CONTENT EVALUATION FOR ROAD-SURFACES MONITORING BY GPR IMAGE AND data processing ON MOBILE PLATFORMS 3

MOISTURE CONTENT EVALUATION FOR ROAD-SURFACES MONITORING BY ...

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3rd international conference on Future Internet of Things and Cloud (FiCloud) / international conference on Open and Big data (OBD)

作者： Benedetto, Francesco Tedeschi, Antonio Univ Rome Tre Signal Proc Telecommun & Econ Lab SP4TE I-00146 Rome Italy

ISBN: (纸本)9781467381031

This work introduces a mobile application for moisture content evaluation aimed at road-surfaces monitoring. Our application exploits Ground Penetrating Radar (GPR) image and data processing in real-time on Android platforms. GPR is one of the most advanced technology in civil engineering applications for road pavement monitoring, while water intrusion in structural layers is one of the most relevant causes of damage of road-surfaces. The novelty of this work (that is the power of our application) is to show the consistency of the GPR diagnosis regarding these hidden conditions, implementing GPR image and data processing on smartphones and tablet computers.

关键词： Android handheld devices mobile applications Ground Penetrating Radar (GPR) data processing moisture content evaluation road surface monitoring

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Efficient FPGA Implementation of a Convolutional Neural Network for Radar signal processing 3

Efficient FPGA Implementation of a Convolutional Neural Netw...

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IEEE 3rd international conference on Artificial Intelligence Circuits and Systems (AICAS)

作者： Zhang, Jingchi Huang, Yihao Yang, Huanrui Martinez, Michael Hickman, Granger Krolik, Jeffrey Li, Hai Duke Univ Elect & Comp Engn Dept Durham NC 27706 USA

ISBN: (纸本)9781665419130

Although neural networks, especially convolutional neural networks (CNNs), have been successfully applied to many domains, there have not found many radar applications mainly due to a paucity of available training data. Focusing on fixed-site radars, this work uses in-situ collected data to train a CNN classifier and suppress clutter components that allow targets to "hide in plain sight." This paper describes a software and hardware co-design approach for implementing a neural network to improve radar signal processing. At the algorithm level, we propose using the ResNet10 model structure and other optimizations trained using the angle-Doppler spectrum of returns at each range. The FPGA implementation is then carefully optimized to better tradeoff performance and energy efficiency. Experimental results show our approach achieves better performance than conventional methods and exceed the requirement by more than 2.5x. Meanwhile our energy consumption is much lower than other platforms like GPU. Our optimization methods can be applied to other CNN structures for efficiency improvement.

关键词： array processing CNN energy consumption FPGA radar signal processing

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Just-in-time Parsing with Scannerless Earley Virtual Machines 3

Just-in-time Parsing with Scannerless Earley Virtual Machine...

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3rd international conference on Vision, Image and signal processing (ICVISP)

作者： Saikunas, Audrius Inst Data Sci & Digital Technol Vilnius Lithuania

ISBN: (纸本)9781450376259

Scannerless Earley Virtual Machines (SEVM) is a new generalized context-free parsing method, in which grammars are internally encoded using a special instruction intermediate language. In this paper we show how just-in-time compilation can be used to translate intermediate form grammars into native machine code to achieve improved parsing performance. We also present an efficient method for lexical disambiguation, which additionally enables to significantly reduce the amount of code that needs to be just-in-time compiled. Finally, we compare our implementation of SEVM with other parser implementations and show that our parser provides acceptable performance for analysing real-world computer languages.

关键词： Parsing Scannerless parsing Just-in-time compiler Virtual machine

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Feature extraction and analysis of speech signal based on fractional Fourier transform 3

Feature extraction and analysis of speech signal based on fr...

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3rd IEEE international conference on Power, Electronics and Computer Applications, ICPECA 2023

作者： Zhai, Yueying Wuhan Qingchuan University Wuhan430000 China

ISBN: (纸本)9781665472784

As an analog signal carrying specific information, voice has become an important means of obtaining and disseminating information in people's social life. The purpose of speech signal processing is to extract effective speech information in complex speech environment. Speech signal has a strong time-varying characteristics. In a short time interval, the characteristics of speech signal can be regarded as basically unchanged, which is an important starting point of speech signal processing. The rate of speech recognition also depends on the accuracy and robustness of Speech signal feature extraction. Therefore, Speech signal feature extraction plays an important role in speech signal processing applications. By comparing the time-frequency resolution of Fourier transform and fractional Fourier transform in noisy background, the unique advantages of fractional Fourier transform to frequency-varying signals are further clarified. © 2023 IEEE.

关键词： Feature extraction

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Anti interference transmission algorithm of wireless communication data in the last kilometer of substation 3

Anti interference transmission algorithm of wireless communi...

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3rd international conference on Intelligent Control, Measurement and signal processing and Intelligent Oil Field, ICMSP 2021

作者： Zhai, Zhuxin Yan, Xin Dongguan Power Supply Bureau of Guangdong Power Grid Co. Ltd. Dongguan China

ISBN: (纸本)9781665437158

The interference of wireless communication data in the last kilometer of substation is becoming more and more serious, so reliable anti-interference transmission mode is needed to ensure data security. The traditional anti-interference transmission algorithm is prone to collision of communication frequency points, which affects the convergence speed of the algorithm. According to the carrier frequency of the interference signal, the cyclic cumulant of the signal is calculated. The poor channel state is regarded as the equivalent interference, and the distribution characteristics of the channel equivalent interference are determined. The frequency band occupation of interference signal is expressed as state, the data interference avoidance model of wireless communication is established, the channel quality is evaluated, and the anti-interference transmission algorithm is designed to improve the reliability of wireless communication process. The experimental results show that the average number of iterations of the proposed anti-interference transmission algorithm is smaller, and the convergence speed is better than the traditional algorithm, which can realize the effective transmission of wireless communication data. © 2021 IEEE.

关键词： signal interference

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Kinship Verification using Color Features and Extreme Learning Machine 3

Kinship Verification using Color Features and Extreme Learni...

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IEEE 3rd international conference on signal and Image processing (ICSIP)

作者： Wu, Xiaoting Feng, Xiaoyi Boutellaa, Elhocine Hadid, Abdenour Univ Oulu Ctr Machine Vis & Signal Anal Oulu Finland Northwestern Polytech Univ Sch Elect & Informat Xian Shaanxi Peoples R China

ISBN: (纸本)9781538663967

Kinship verification from faces is a challenging task that is attracting an increasing attention in the recent years. The proposed methods so far are not robust enough to predict the kin between persons via facial appearance only. The initial studies using deep convolutional neural networks (CNN) have not shown their full potential as well, mainly due to limited training data. To mitigate this problem, we propose a new approach to kinship verification based on color features and extreme learning machines (ELM). While ELM aims to deal with small size training sets, color features are proven to provide significant enhancement over gray-scale counterparts. We evaluate our proposed method on three benchmark and publicly available kinship databases, namely KinFaceW-I, KinFaceW-II and TSKinFace. The obtained results compares favorably against some state-of-the-art methods including those based on deep learning.

关键词： kinship verification color features extreme learning machine

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