Relevant bibliographies by topics / Wavelets and fast transform eavelet

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Academic literature on the topic 'Wavelets and fast transform eavelet'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "Wavelets and fast transform eavelet"

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Stolarek, J. "Adaptive synthesis of a wavelet transform using fast neural network." Bulletin of the Polish Academy of Sciences: Technical Sciences 59, no. 1 (2011): 9–13. http://dx.doi.org/10.2478/v10175-011-0002-5.

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Adaptive synthesis of a wavelet transform using fast neural network This paper introduces a new method for an adaptive synthesis of a wavelet transform using a fast neural network with a topology based on the lattice structure. The lattice structure and the orthogonal lattice structure are presented and their properties are discussed. A novel method for unsupervised training of the neural network is introduced. The proposed approach is tested by synthesizing new wavelets with an expected energy distribution between low- and high-pass filters. Energy compaction of the proposed method and Daubec
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Wu, Jiasong, Fuzhi Wu, Qihan Yang, et al. "Fractional Spectral Graph Wavelets and Their Applications." Mathematical Problems in Engineering 2020 (November 6, 2020): 1–18. http://dx.doi.org/10.1155/2020/2568179.

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One of the key challenges in the area of signal processing on graphs is to design transforms and dictionary methods to identify and exploit structure in signals on weighted graphs. In this paper, we first generalize graph Fourier transform (GFT) to spectral graph fractional Fourier transform (SGFRFT), which is then used to define a novel transform named spectral graph fractional wavelet transform (SGFRWT), which is a generalized and extended version of spectral graph wavelet transform (SGWT). A fast algorithm for SGFRWT is also derived and implemented based on Fourier series approximation. Som
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Li, Yaoguo, and Douglas W. Oldenburg. "Rapid construction of equivalent sources using wavelets." GEOPHYSICS 75, no. 3 (2010): L51—L59. http://dx.doi.org/10.1190/1.3378764.

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We have developed a fast algorithm for generating an equivalent source by using fast wavelet transforms based on orthonormal, compactly supported wavelets. We apply a 2D wavelet transform to each row and column of the coefficient matrix and subsequently threshold the transformed matrix to generate a sparse representation in the wavelet domain. The algorithm then uses this sparse matrix to construct the the equivalent source directly in the wavelet domain. Performing an inverse wavelet transform then yields the equivalent source in the space domain. Using upward continuation of total-field magn
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Toda, Hiroshi, Zhong Zhang, and Takashi Imamura. "Practical design of perfect-translation-invariant real-valued discrete wavelet transform." International Journal of Wavelets, Multiresolution and Information Processing 12, no. 04 (2014): 1460005. http://dx.doi.org/10.1142/s0219691314600054.

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The real-valued tight wavelet frame having perfect translation invariance (PTI) has already proposed. However, due to the irrational-number distances between wavelets, its calculation amount is very large. In this paper, based on the real-valued tight wavelet frame, a practical design of a real-valued discrete wavelet transform (DWT) having PTI is proposed. In this transform, all the distances between wavelets are multiples of 1/4, and its transform and inverse transform are calculated fast by decomposition and reconstruction algorithms at the sacrifice of a tight wavelet frame. However, the r
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Cheriet, Leyla, Salah Chenikher, and Karima Boukari. "Fast motion estimation algorithm based on geometric wavelet transform." International Journal of Wavelets, Multiresolution and Information Processing 17, no. 04 (2019): 1950018. http://dx.doi.org/10.1142/s0219691319500188.

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Motion estimation is a means, which consists in studying the displacement of objects in a video sequence, seeking the correlation between two successive frames, to predict the change in the contents position. Motion estimation is becoming a progressively significant requirement in a variety of applications such as medicine, robotics and video compression. In recent years, wavelets are effective tools for motion estimation, but the DWT (Discrete Wavelet Transform) will suffer from problems like translation sensitivity, poor directionality and absence of phase information. These three disadvanta
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Irfan, Nagma, and A. H. Siddiqi. "A Wavelet Algorithm for Fourier-Bessel Transform Arising in Optics." International Journal of Engineering Mathematics 2015 (August 31, 2015): 1–9. http://dx.doi.org/10.1155/2015/789675.

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The aim of the paper is to propose an efficient and stable algorithm that is quite accurate and fast for numerical evaluation of the Fourier-Bessel transform of order ν, ν>-1, using wavelets. The philosophy behind the proposed algorithm is to replace the part tf(t) of the integral by its wavelet decomposition obtained by using CAS wavelets thus representing Fν(p) as a Fourier-Bessel series with coefficients depending strongly on the input function tf(t). The wavelet method indicates that the approach is easy to implement and thus computationally very attractive.
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Stolarek, Jan. "Improving energy compaction of a wavelet transform using genetic algorithm and fast neural network." Archives of Control Sciences 20, no. 4 (2010): 417–33. http://dx.doi.org/10.2478/v10170-010-0024-5.

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Improving energy compaction of a wavelet transform using genetic algorithm and fast neural networkIn this paper a new method for adaptive synthesis of a smooth orthogonal wavelet, using fast neural network and genetic algorithm, is introduced. Orthogonal lattice structure is presented. A new method of supervised training of fast neural network is introduced to synthesize a wavelet with desired energy distribution between output signals from low-pass and high-pass filters on subsequent levels of a Discrete Wavelet Transform. Genetic algorithm is proposed as a global optimization method for defi
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Abeyratne, M. K., W. Freeden, and C. Mayer. "Multiscale deformation analysis by Cauchy-Navier wavelets." Journal of Applied Mathematics 2003, no. 12 (2003): 605–45. http://dx.doi.org/10.1155/s1110757x03206033.

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A geoscientifically relevant wavelet approach is established for the classical (inner) displacement problem corresponding to a regular surface (such as sphere, ellipsoid, and actual earth surface). Basic tools are the limit and jump relations of (linear) elastostatics. Scaling functions and wavelets are formulated within the framework of the vectorial Cauchy-Navier equation. Based on appropriate numerical integration rules, a pyramid scheme is developed providing fast wavelet transform (FWT). Finally, multiscale deformation analysis is investigated numerically for the case of a spherical bound
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Grohs, Philipp, Željko Kereta, and Uwe Wiesmann. "A shearlet-based fast thresholded Landweber algorithm for deconvolution." International Journal of Wavelets, Multiresolution and Information Processing 14, no. 05 (2016): 1650032. http://dx.doi.org/10.1142/s0219691316500326.

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Image deconvolution is an important problem, which has seen plenty of progress in the last decades. Due to its ill-posedness, a common approach is to formulate the reconstruction as an optimization problem[Formula: see text] regularized by an additional sparsity-enforcing term. This term is often modeled as an [Formula: see text] norm measured in the domain of a suitable signal transform. The resulting optimization problem can be solved by an iterative approach via Landweber iterations with soft thresholding of the transform coefficients. Previous approaches focused on thresholding in the wave
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Goyal, Er Neha. "Implementation of Image Compression using fast Wavelet Transform using HAAR and Daubechies Wavelets." IOSR Journal of Engineering 02, no. 11 (2012): 18–24. http://dx.doi.org/10.9790/3021-021121824.

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Dissertations / Theses on the topic "Wavelets and fast transform eavelet"

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Barbosa, Francisco M?rcio. "Estudo da transformada r?pida wavelet e sua conex?o com banco de filtros." Universidade Federal do Rio Grande do Norte, 2008. http://repositorio.ufrn.br:8080/jspui/handle/123456789/17002.

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Made available in DSpace on 2014-12-17T15:26:36Z (GMT). No. of bitstreams: 1 FranciscoMB.pdf: 1735858 bytes, checksum: 1307c69bd6f2b893c3fd27379c0533db (MD5) Previous issue date: 2008-09-17<br>In this work we presented an exhibition of the mathematical theory of orthogonal compact support wavelets in the context of multiresoluction analysis. These are particularly attractive wavelets because they lead to a stable and very efficient algorithm, that is Fast Transform Wavelet (FWT). One of our objectives is to develop efficient algorithms for calculating the coefficients wavelet (FWT) through t
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Guevara, Escobedo Jorge. "Embebed wavelet image reconstruction in parallel computation hardware." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/embebed-wavelet-image-reconstruction-in-parallel-computation-hardware(fdb646f4-8090-4a08-974e-d854adc6bff7).html.

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In this thesis an algorithm is demonstrated for the reconstruction of hard-field Tomography images through localized block areas, obtained in parallel and from a multiresolution framework. Block areas are subsequently tiled to put together the full size image. Given its properties to preserve its compact support after being ramp filtered, the wavelet transform has received to date much attention as a promising solution in radiation dose reduction in medical imaging, through the reconstruction of essentially localised regions. In this work, this characteristic is exploited with the aim of reduc
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"Parallelization of fast wavelet transform." Chinese University of Hong Kong, 1994. http://library.cuhk.edu.hk/record=b5895460.

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Shum Yu Hing.<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 1994.<br>Includes bibliographical references (leaves 140-143).<br>ABSTRACT --- p.1<br>Chapter 1. --- INTRODUCTION<br>Chapter 1.1. --- Fourier Analysis --- p.3<br>Chapter 1.2. --- Wavelet Analysis --- p.6<br>Chapter 1.3. --- Parallelization --- p.10<br>Chapter 1.3.1. --- Data Dependency Analysis<br>Chapter 2. --- LITERATURE SURVEY<br>Chapter 2.1. --- One Dimensional Fast Wavelet Transform (Discrete) --- p.13<br>Chapter 2.2. --- Shared Memory Architecture : Parallel Virtual Machine (PVM)<br>Chapter 2.3. --- Distributed Memo
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"Fast Numerical Algorithms for 3-D Scattering from PEC and Dielectric Random Rough Surfaces in Microwave Remote Sensing." Doctoral diss., 2016. http://hdl.handle.net/2286/R.I.38433.

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abstract: We present fast and robust numerical algorithms for 3-D scattering from perfectly electrical conducting (PEC) and dielectric random rough surfaces in microwave remote sensing. The Coifman wavelets or Coiflets are employed to implement Galerkin’s procedure in the method of moments (MoM). Due to the high-precision one-point quadrature, the Coiflets yield fast evaluations of the most off-diagonal entries, reducing the matrix fill effort from O(N^2) to O(N). The orthogonality and Riesz basis of the Coiflets generate well conditioned impedance matrix, with rapid convergence for the conjug
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Hulett, David Alexander. "De Fourier a wavelets : un breve recorrido por el análisis tiempo-frecuencia." Bachelor's thesis, 2020. http://hdl.handle.net/11086/15941.

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Tesis (Lic. en Matemática)--Universidad Nacional de Córdoba, Facultad de Matemática, Astronomía, Física y Computación, 2020.<br>Un pequeño tour por el análisis de Fourier. Definimos a la transformada continua de Fourier, presentamos y estudiamos los resultados principales de la serie de Fourier y de la transformada de Fourier discreta. Analizamos cómo hacer la transición de serie a transformada continua y de transformada discreta a la serie. Para estudiar la estructura tiempo-frecuencia de una función presentamos a las transformadas atómicas y estudiamos dos ejemplos: la STFT y la transformada
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Book chapters on the topic "Wavelets and fast transform eavelet"

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Gomes, Jonas, and Luiz Velho. "The Fast Wavelet Transform." In From Fourier Analysis to Wavelets. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22075-8_7.

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Abbate, Agostino, Casimer M. DeCusatis, and Pankaj K. Das. "Discrete Wavelet Transform: From Frames to Fast Wavelet Transform." In Wavelets and Subbands. Birkhäuser Boston, 2002. http://dx.doi.org/10.1007/978-1-4612-0113-7_4.

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Bonnet, Pierre, and Didier Remond. "Discrete Wavelets and Fast Wavelet Transform." In Analysis of Controlled Dynamical Systems. Birkhäuser Boston, 1991. http://dx.doi.org/10.1007/978-1-4612-3214-8_8.

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"Fast Fourier Transform." In Elements of Wavelets for Engineers and Scientists. John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471668885.ch7.

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"The Fast Fourier Transform." In The World According to Wavelets. A K Peters/CRC Press, 1998. http://dx.doi.org/10.1201/9781439864555-20.

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"The Fast Wavelet Transform." In The World According to Wavelets. A K Peters/CRC Press, 1998. http://dx.doi.org/10.1201/9781439864555-24.

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"Fast Gamblet Transform." In Operator-Adapted Wavelets, Fast Solvers, and Numerical Homogenization. Cambridge University Press, 2019. http://dx.doi.org/10.1017/9781108594967.021.

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Gebremeskel, Gebeyehu Belay, Yi Chai, Zhou Shangbo, and Su Xu. "Image Data Mining Based on Wavelet Transform for Visualization of the Unique Characteristics of Image Data." In Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition, Analysis, and Image Processing. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-8654-0.ch001.

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Mining techniques can play an important role in image decomposition, segmentation, classification and retrieval systems. As image data become more complex and growing at a fast pace, searching valuable information and knowledge implicit become more challenging than ever before. In this chapter, authors proposed a WT based DM techniques to optimize and characterize the unique feature of image retrieval, which is fundamental to optimize informative mathematical representation of image objects. Many software, including data exploratory tools such as DM packages contain fast and efficient programs that perform WT. Wavelets have quickly gained popularity among scientists and engineers, both in theoretical research and in applications. The authors discussed in details and introduced a novel method for image database analysis in different scenarios that foster the wide access of image data.
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Gebremeskel, Gebeyehu Belay, Yi Chai, Zhou Shangbo, and Su Xu. "Image Data Mining Based on Wavelet Transform for Visualization of the Unique Characteristics of Image Data." In Biometrics. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-0983-7.ch018.

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Mining techniques can play an important role in image decomposition, segmentation, classification and retrieval systems. As image data become more complex and growing at a fast pace, searching valuable information and knowledge implicit become more challenging than ever before. In this chapter, authors proposed a WT based DM techniques to optimize and characterize the unique feature of image retrieval, which is fundamental to optimize informative mathematical representation of image objects. Many software, including data exploratory tools such as DM packages contain fast and efficient programs that perform WT. Wavelets have quickly gained popularity among scientists and engineers, both in theoretical research and in applications. The authors discussed in details and introduced a novel method for image database analysis in different scenarios that foster the wide access of image data.
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Zakaria, Jamaluddin, and Mohd Fadzli Mohd Salleh. "Wavelet Based Multicarrier Modulation (MCM) Systems: PAPR Analysis." In Wavelet Theory [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.94579.

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Orthogonal frequency division multiplexing (OFDM) is a prominent system in transmitting multicarrier modulation (MCM) signals over selective fading channel. The system offers to attain a higher degree of bandwidth efficiency, higher data transmission, and robust to narrowband frequency interference. However, it incurs a high peak-to-average power ratio (PAPR) where the signals work in the nonlinear region of the high-power amplifier (HPA) results in poor performance. Besides, an attractive dynamic wavelet analysis and its derivatives such as wavelet packet transform (WPT) demonstrates almost the same criteria as the OFDM in MCM system. Wavelet surpasses Fourier based analysis by inherent flexibility in terms of windows function for non-stationary signal. In wavelet-based MCM systems (wavelet OFDM (WOFDM) and Wavelet packet OFDM (WP-OFDM)), the constructed orthogonal modulation signals behaves similar to the fast Fourier transform (FFT) does in the conventional OFDM (C-OFDM) system. With no cyclic prefix (CP) need to be applied, these orthogonal signals hold higher bandwidth efficiency. Hence, this chapter presents a comprehensive study on the manipulation of specified parameters using WP-OFDM, WOFDM and C-OFDM signals together with various wavelets under the additive white Gaussian noise (AWGN) channel.
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Conference papers on the topic "Wavelets and fast transform eavelet"

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Guo, Haitao, and C. Sidney Burrus. "Fast approximate Fourier transform via wavelets transform." In SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, edited by Michael A. Unser, Akram Aldroubi, and Andrew F. Laine. SPIE, 1996. http://dx.doi.org/10.1117/12.255236.

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Gumah, Mohamed E., Etienne Schneider, and Abdurazzag Ali Aburas. "Handwriting recognition system using fast wavelets transform." In 2010 International Symposium on Information Technology (ITSim 2010). IEEE, 2010. http://dx.doi.org/10.1109/itsim.2010.5561302.

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Afdhal, Rim, Ridha Ejbali, Mourad Zaied, and Chokri Ben Amar. "Emotion recognition using features distances classified by wavelets network and trained by fast wavelets transform." In 2014 14th International Conference on Hybrid Intelligent Systems (HIS). IEEE, 2014. http://dx.doi.org/10.1109/his.2014.7086205.

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Jauregui, Juan C., Eduardo Rubio, and Oscar Gonzalez. "Non-Linear Rotor-Rubbing Vibration Analysis Through the Wavelet Transform." In ASME Turbo Expo 2007: Power for Land, Sea, and Air. ASMEDC, 2007. http://dx.doi.org/10.1115/gt2007-27417.

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Vibration analysis is the basis for an early detection of faults in rotating machinery. It is the main element for any maintenance program. Due to the basics of the FFT (Fast Fourier Transform), vibration prediction systems based on this analysis tool are unable to identify unsteady and non-linear vibrations. They provide only the spectrum content of a signal, but due to its nature, the time interval and the instant when the vibration occurs are eliminated. Therefore, new modern signal analysis tools have been developed. Among them, wavelets have been extensively applied to non-linear vibratio
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Liaghat, M., A. Abdollahi, F. Daneshmand, and T. Liaghat. "Wavelet Analysis of the Pressure Fluctuations of Bottom Outlet of Kamal-Saleh Dam." In ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-12745.

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Non-stationary signals are frequently encountered in a variety of engineering fields. The inability of conventional Fourier analysis to preserve the time dependence and describe the evolutionary spectral characteristics of non-stationary processes requires tools which allow time and frequency localization beyond customary Fourier analysis. The spectral analysis of non-stationary signals cannot describe the local transient features due to averaging over the duration of the signal [1]. The Fourier Transform (FT) and the short time Fourier transform (STFT) have been often used to measure transien
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Bonel-Cerdan, Jose I., and Jorgen L. Nikolajsen. "An Introduction to Harmonic Wavelet Analysis of Machine Vibrations." In ASME 1997 International Gas Turbine and Aeroengine Congress and Exhibition. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/97-gt-058.

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The Fast Wavelet Transform (FWT) is a powerful new tool which can be used for vibration analysis and condition monitoring of advanced rotating machinery. The main advantage of wavelet analysis for condition monitoring is that so-called wavelet maps can be produced showing three dimensional plots of amplitude versus frequency and time. This is in contrast to Fast Fourier Transform (FFT) analysis, in which the time domain of the signal is lost. The wavelet maps provide striking visual indications of tiny changes in machine behaviour which cannot be detected in a normal frequency spectrum. This i
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