Acoustic signals

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  • Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Blind Separation of Acoustic Signals Combining SIMO-Model-Based Independent Component Analysis and Binary Masking

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  • Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí lâm nghiệp đề tài: Xylem acoustic signals from mature Pinus sylvestris during an extended drought...

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  • The basic idea behind any sonar system is as follows: an acoustic signal (or ping) is emitted by the sonar into an area to be observed; the sonar then listens for echoes of the ping that have been produced when bouncing back from the objects that might be present in the area. Typically, sonar images are produced by plotting the intensity measured back by the sonar versus time, and since the speed of sound underwater is known (or can be measured), the time axis effectively corresponds to range from the sonar. In this way, just as light illuminates a scene...

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  • Conclusions References In this chapter we review properties of auditory perception that are relevant to the design of coders for acoustic signals. The chapter begins with a general definition of a

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  • The science of acoustics deals with the creation of sound, sound transmission through solids, and the effects of sound on both inert and living materials. As a mechanical effect, sound is essentially the passage of pressure fluctuations through matter as the result of vibrational forces acting on that medium. Sound possesses the attributes of wave phenomena, as do light and radio signals. But unlike its electromagnetic counterparts, sound cannot travel through a vacuum.

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  • We address the task of unsupervised topic segmentation of speech data operating over raw acoustic information. In contrast to existing algorithms for topic segmentation of speech, our approach does not require input transcripts. Our method predicts topic changes by analyzing the distribution of reoccurring acoustic patterns in the speech signal corresponding to a single speaker. The algorithm robustly handles noise inherent in acoustic matching by intelligently aggregating information about the similarity profile from multiple local comparisons. ...

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  • Sound emission (AE) is one of the most important test non-destructive (NDT) methods of materials, construction and machinery. The sound emission method with most other technical non-destructive testing in two important respects. first of all, the signal source is always located inside the investigated materials / structures. The second important thing is the NDT method to detect geometrical discontinuities, while emission sound motion detection errors.

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  • Biological signal analysis1 encompasses several interdisciplinary topics that deal with analysing signals generated by various physiological processes in the human body. These signals could be electrical, chemical or acoustic in origin and an analysis of these signals are often useful in explaining and/or identifying pathological conditions of the human body. However, these signals in their rawest form do not provide much information and therefore, the motivation behind biological signal analysis is to extract (i.e. to reveal) the relevant information.

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  • Independent Component Analysis (ICA) is a signal-processing method to extract independent sources given only observed data that are mixtures of the unknown sources. Recently, Blind Source Separation (BSS) by ICA has received considerable attention because of its potential signal-processing applications such as speech enhancement systems, image processing, telecommunications, medical signal processing and several data mining issues.

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  • Estimating bearings of multiple narrowband signals from measurements collected by an array of sensors has been a very active research problem for the last two decades. Typical applications of this problem are radar, communication, and underwater acoustics. Many algorithms have been proposed to solve the bearing estimation

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  • Introduction: Dereverberation Using Microphone Arrays An acoustic enclosure usually reduces the intelligibility of the speech transmitted through it because the transmission path is not ideal. Apart from the direct signal from the source, the sound is also reflected off one or more surfaces (usually walls) before reaching the receiver. The resulting signal can be viewed as the output of a

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  • EURASIP Journal on Applied Signal Processing 2003:3, 276–286 c 2003 Hindawi Publishing Corporation Robust Clustering of Acoustic Emission Signals Using Neural Networks and Signal Subspace Projections Vahid Emamian Department of Electrical & Computer Engineering, University of Minnesota, 200 Union St. SE, Minneapolis, MN 55455, USA Email: emamian@ieee.org Mostafa Kaveh Department of Electrical & Computer Engineering, University of Minnesota, 200 Union St. SE, Minneapolis, MN 55455, USA Email: mos@ece.umn.edu Ahmed H.

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  • With the advent of multimedia, digital signal processing (DSP) of sound has emerged from the shadow of bandwidth-limited speech processing. Today, the main applications of audio DSP are high quality audio coding and the digital generation and manipulation of music signals. They share common research topics including perceptual measurement techniques and analysis/synthesis methods. Smaller but nonetheless very important topics are hearing aids using signal processing technology and hardware architectures for digital signal processing of audio.

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  • EURASIP Journal on Applied Signal Processing 2003:11, 1091–1109 c 2003 Hindawi Publishing Corporation Exploiting Acoustic Similarity of Propagating Paths for Audio Signal Separation Bin Yin Faculty of Electrical Engineering, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands Storage Signal Processing Group, Philips Research Laboratories, P.O. Box WY-31, 5656 AA Eindhoven, The Netherlands Email: bin.yin@philips.com Piet C. W. Sommen Faculty of Electrical Engineering, Eindhoven University of Technology, P.O.

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  • EURASIP Journal on Applied Signal Processing 2003:7, 668–675 c 2003 Hindawi Publishing Corporation Joint Acoustic and Modulation Frequency Les Atlas Department of Electrical Engineering, Box 352500, Seattle, WA 98195-2500, USA Email: atlas@ee.washington.edu Shihab A. Shamma Department of Electrical and Computer Engineering and Center for Auditory and Acoustic Research, Institute for Systems Research, University of Maryland, College Park, MD 20742, USA Email: sas@eng.umd.

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  • EURASIP Journal on Applied Signal Processing 2003:7, 617–619 c 2003 Hindawi Publishing Corporation Editorial Shihab A. Shamma Department of Electrical and Computer Engineering and Center for Auditory and Acoustic Research, Institute for Systems Research, University of Maryland, College Park, MD 20742, USA Email: sas@eng.umd.edu ´ Andre van Schaik School of Electrical and Information Engineering, University of Sydney, Sydney, NSW 2006, Australia Email: andre@ee.usyd.edu.

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  • Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Vesa Valimaki Laboratory of Acoustics and Audio Signal Processing,

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  • EURASIP Journal on Applied Signal Processing 2003:11, 1053–1055 c 2003 Hindawi Publishing Corporation Editorial Kees Janse Digital Signal Processing Group, Philips Research Laboratories, Prof. Holstlaan 4 (WY81), 5656 AA Eindhoven, The Netherlands Email: kees.janse@philips.com Walter Kellermann Multimedia Communications and Signal Processing, Friedrich-Alexander University of Erlangen-Nuremberg, Cauerstrasse 7, 91058 Erlangen, Germany Email: wk@LNT.

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  • EURASIP Journal on Applied Signal Processing 2003:10, 953–967 c 2003 Hindawi Publishing Corporation Frequency-Zooming ARMA Modeling for Analysis of Noisy String Instrument Tones Paulo A. A. Esquef Laboratory of Acoustics and Audio Signal Processing, Helsinki University of Technology, P.O. Box 3000, FIN-02015 HUT, Espoo, Finland Email: paulo.esquef@hut.fi Matti Karjalainen Laboratory of Acoustics and Audio Signal Processing, Helsinki University of Technology, P.O. Box 3000, FIN-02015 HUT, Espoo, Finland Email: matti.karjalainen@hut.

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  • EURASIP Journal on Applied Signal Processing 2003:8, 814–823 c 2003 Hindawi Publishing Corporation On the Use of Evolutionary Algorithms to Improve the Robustness of Continuous Speech Recognition Systems in Adverse Conditions Sid-Ahmed Selouani Secteur Gestion de l’Information, Universit´ de Moncton, Campus de Shippagan, 218 boulevard J.-D.-Gauthier, e Shippagan, Nouveau-Brunswick, Canada E8S 1P6 Email: selouani@umcs.

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