Relevant bibliographies by topics / NON-LINEAR SIGNAL PROCESSING

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'NON-LINEAR SIGNAL PROCESSING'

Author: Grafiati
Published: 11 September 2023

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Journal articles on the topic "NON-LINEAR SIGNAL PROCESSING"

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Pagès-Zamora, Alba, and Miguel A. Lagunas. "Fourier models for non-linear signal processing." Signal Processing 76, no. 1 (July 1999): 1–16. http://dx.doi.org/10.1016/s0165-1684(98)00243-6.

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Qu, Yanhuai, Shuai Zhang, and Qingkai Han. "Comparison of Non-linear Signals Analysis Methods." MATEC Web of Conferences 232 (2018): 01014. http://dx.doi.org/10.1051/matecconf/201823201014.

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In modern engineering, linear is relative, while non-linear and non-stationary is absolute. There are many methods in non-linear signals processing. How to select a most suitable analysis method quickly for the nonlinear signal is particularly important, which can improve the signal processing efficiently. In this paper, three common analysis methods for nonlinear signals, Wavelet spectrum, Hilbert spectral analysis (HSA) and Poincaré mapping are researched and analyzed by some typical nonlinear signals from the complex electromechanical model test system. The effectiveness and application scopes of these approaches are obtained, which can provide a theoretical and practical basis for engineering application.
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Lunner, Thomas, Johan Hellgren, Stig Arlinger, and Claus Elberling. "Non-Linear Signal Processing in Digital Hearing Aids." Scandinavian Audiology 27, no. 4 (January 1998): 40–49. http://dx.doi.org/10.1080/010503998420649.

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Bhateja, Vikrant, Rishendra Verma, Rini Mehrotra, and Shabana Urooj. "A Non-Linear Approach to ECG Signal Processing using Morphological Filters." International Journal of Measurement Technologies and Instrumentation Engineering 3, no. 3 (July 2013): 46–59. http://dx.doi.org/10.4018/ijmtie.2013070104.

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Analysis of the Electrocardiogram (ECG) signals is the pre-requisite for the clinical diagnosis of cardiovascular diseases. ECG signal is degraded by artifacts such as baseline drift and noises which appear during the acquisition phase. The effect of impulse and Gaussian noises is randomly distributed whereas baseline drift generally affects the baseline of the ECG signal; these artifacts induce interference in the diagnosis of cardio diseases. The influence of these artifacts on the ECG signals needs to be removed by suitable ECG signal processing scheme. This paper proposes combination of non linear morphological operators for the noise and baseline drift removal. Non flat structuring elements of varying dimensions are employed with morphological filtering to achieve low distortion as well as good noise removal. Simulation outcomes illustrate noteworthy improvement in baseline drift yielding lower values of MSE and PRD; on the other hand high signal to noise ratios depicts suppression of impulse and Gaussian noises.
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Adithya valli, N., and Dr D. Elizabath Rani. "Modified PWNLFM Signal for Side-Lobe Reduction." International Journal of Engineering & Technology 7, no. 4.20 (November 28, 2018): 4. http://dx.doi.org/10.14419/ijet.v7i4.20.22110.

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Many applications in radar systems require low range side-lobe performance which is achieved by pulse compression processing. Most used chirp signal for this processing is linear frequency modulation (LFM) signal but with a presence of first high side-lobe level. Suppression of this side-lobe requires weighting function causing the reduction in signal to noise ratio at the receiver owing to mismatch loss. Non-linear chirp signals are introduced as a solution and became most practiced signals aimed at reducing side-lobes. In this paper, an overall piece wise non-linear frequency modulation chirp signal is designed by merging two stages, one with linear function and the other with a tangent based non-linear function. Simulation results show significant reduction in the sidelobe level of autocorrelation function when NLFM is generated in this method.
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BILLINGS, S. A., and Q. H. TAO. "Model validity tests for non-linear signal processing applications." International Journal of Control 54, no. 1 (July 1991): 157–94. http://dx.doi.org/10.1080/00207179108934155.

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Liu, H., and T. Vinh. "Multi-dimensional signal processing for non-linear structural dynamics." Mechanical Systems and Signal Processing 5, no. 1 (January 1991): 61–80. http://dx.doi.org/10.1016/0888-3270(91)90015-w.

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Smolarik, Lukas, Dusan Mudroncik, and Lubos Ondriga. "ECG Signal Processing." Advanced Materials Research 749 (August 2013): 394–400. http://dx.doi.org/10.4028/www.scientific.net/amr.749.394.

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Electrocardiography (ECG) is a diagnostic method that allows sensing and record the electric activity of heart [. The measurement of electrical activity is used as a standard twelve-point system. At each of these leads to measure the useful signal and interference was measured. The intensity of interference depends on the artefacts (electrical lines, brum, motion artefacts, muscle, interference from the environment, etc.). For correct evaluation of measured signal there is a need to processing the measured signal to suitable form. At present, the use of electrocardiograms with sensors with contact scanning are difficult to set a time so we decided to use the principle of non-contact sensing. Such a device to measure the ECG was constructed under the project. The disadvantage of such devices is a problem with a high level of noise, which degrades a useful signal. The aim of this article is to pre-process the signals obtained from non-contact sensing. The contactless devices are powered from the network and battery. The electrodes were connected by way of Eithoven bipolar leads. Signals were pre-treated with suitable filters so that they are also appropriate for their subsequent analysis. In the filtration ECG signals was used as a method of linear (low pass filter, high pass, IIR (Infinite Impulse Response) peak, notch filter. The results of many signals clearly demonstrate removing noise in the ECG signals to the point that is also suitable for their analysis.
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Bilgehan, Bülent. "Efficient approximation for linear and non‐linear signal representation." IET Signal Processing 9, no. 3 (May 2015): 260–66. http://dx.doi.org/10.1049/iet-spr.2014.0070.

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Kumar, R. Suresh, and P. Manimegalai. "Detection and Separation of Eeg Artifacts Using Wavelet Transform." International Journal of Informatics and Communication Technology (IJ-ICT) 7, no. 3 (December 1, 2018): 149. http://dx.doi.org/10.11591/ijict.v7i3.pp149-156.

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Bio-medical signal processing is one of the most important techniques of multichannel sensor network and it has a substantial concentration in medical application. However, the real-time and recorded signals in multisensory instruments contains different and huge amount of noise, and great work has been completed in developing most favorable structures for estimating the signal source from the noisy signal in multichannel observations. Methods have been developed to obtain the optimal linear estimation of the output signal through the Wide-Sense-Stationary (WSS) process with the help of time-invariant filters. In this process, the input signal and the noise signal are assumed to achieve the linear output signal. During the process, the non-stationary signals arise in the bio-medical signal processing in addition to it there is no effective structure to deal with them. Wavelets transform has been proved to be the efficient tool for handling the non-stationary signals, but wavelet provide any possible way to approach multichannel signal processing. Based on the basic structure of linear estimation of non-stationary multichannel data and statistical models of spatial signal coherence acquire through the wavelet transform in multichannel estimation. The above methods can be used for Electroencephalography (EEG) signal denoising through the original signal and then implement the noise reduction technique to evaluate their performance such as SNR, MSE and computation time.
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Dissertations / Theses on the topic "NON-LINEAR SIGNAL PROCESSING"

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Frazer, Gordon John. "Aspects of time-varying non Gaussian non-linear signal analysis." Thesis, Queensland University of Technology, 1996. https://eprints.qut.edu.au/105546/1/T%28BE%26E%29%201032%20Aspects%20of%20time-varying%20non-Gaussian%20non-linear%20signal%20analysis.pdf.

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This thesis addresses problems in the field of time-varying, non-Gaussian, non-linear signal processing. It concentrates on developing results in the areas of time-frequency signal analysis and higher-order spectra which are linked by the developing area of time-varying higher-order spectra. Motivation comes from applying procedures developed to underwater acoustic signals. Reviews of time-frequency analysis and higher-order spectra precede the research contributions. Three appendices cover: a review of the multiple-window spectrum estimation method, an improved procedure for computing analytic signals frequently used in time-frequency signal analysis, and an updated approach for computing Slepian sequences necessary for the multiple-window spectrogram.
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Corbari, Costantino. "Development of non-linear waveguide devices for optical signal processing." Thesis, University of Southampton, 2005. https://eprints.soton.ac.uk/65506/.

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Reported in this thesis are advances in glass poling, a technique which produces second-order optical nonlinearity in glass. Poling of glass has drawn much attention because frequency conversion and electro-optic modulation, operations which are typically restricted to crystals, becomes feasible in glass fibres and waveguides which are widely spread media in photonics thanks to their excellent optical properties and mature manufacturing technology. Poled silica glass, despite showing about 10 times lower second-order nonlinearity than nonlinear crystals, can be competitive with them because longer interaction lengths are possible in glass fibres, owing to the lower chromatic dispersion. -gratings in fibres. This technology led to the first demonstration of an all-fibre frequency doubler of a fibre laser. Milliwatts of red light in the fundamental mode were produced by frequency doubling in a quasi-phase matched periodically poled silica fibre which was directly spliced to the output of the laser source. Efficiency up to 2.5% has been demonstrated in 11.5 cm long device with only about 100W of pump power, which means that 50% conversion efficiency is expected for a 2kW input power.
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Moille, Grégory. "Non-Linear Dynamics in Semiconductor Nano-Structures for Signal Processing." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLS174/document.

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Cette thèse porte sur la numérisation de signaux hyperfréquences en utilisant une horloge optique, possédant une gigue temporelle très faible en comparaison des horloges électroniques. Une faible gigue est un facteur clé de l’échantillonnage à haute performance, car l’horloge commande l’ouverture d’une “porte” qui extrait les échantillons du signal à intervalles réguliers. Cette thèse décrit deux approches originales : l’échantillonnage purement optique et l’échantillonnage électro-optique.Une porte électro-optique se constitue d’une ligne coplanaire transportant le signal électrique. Cette ligne présente une discontinuité qui devient conductrice sur commande optique grâce à un matériau photoconducteur. Les alliages semi-conducteurs du groupe III-V sont souvent utilisés car la mobilité de ces porteurs photo-générés est suffisamment élevée, ce qui est favorable à une bonne conductivité à l’état “on”. Le GaAs, en particulier, présente l’avantage d’une conductivité faible à l’état “off” du fait de la largeur de la bande interdite électronique. Cela explique l’intérêt de ce matériau, cependant, cela impose aussi une contrainte sur la longueur d’onde de la source laser, expliquant l’utilisation de sources autour 800 nm.Dans cette thèse l’utilisation de sources laser à verrouillage de modes à fibre, développées dans le domaine des Télécoms, donc plus facilement accessibles, tout en gardant le GaAs comme matériaux actif est explorée. Cela est possible en exaltant l’efficacité de l’absorption à deux photons, effet faible dans la plupart des structures. L’approche suivie porte sur l’utilisation d’une cavité à cristaux photoniques. Le très fort confinement et le très faible volume occupé par le mode optique se traduit en une très forte absorption non linéaire. De plus, la nano-structuration du semi-conducteur réduit de manière considérable le temps de vie des porteurs, ce qui permet un retour suffisamment rapide à l’état “off”. L’étude se conclut par la démonstration de la fonction d’échantillonnage.La même fonction a été étudiée dans le cas ou le signal hyperfréquence se trouve sur une porteuse optique. La fonction porte “tout optique” est réalisée par un résonateur à cristaux photoniques. La génération de porteurs par absorption à deux photons induit un déplacement spectral de la résonance, ce qui est exploité pour moduler la transmission du dispositif. Une porte optique rapide, capable en principe de traiter des signaux dépassant les 50 GHz à été montrée. Cette porte requiert une puissance de commande de l’ordre de 200 fJ/impulsion, ce qui est suffisamment faible pour utiliser des sources lasers compactes (diode laser) et, de ce fait, outre sa très faible taille, peut être intégrée facilement
This thesis is focused on the digitalization of radio-frequency signal using optical clock, allowing a low time jitter compared to electronic clocks. A low jitter is a key factor for high performance sampling, as the clock commands the “gate” opening which extracts the signal samples at regular intervals. This thesis describes two original approaches: all-optical sampling and electro-optics one.An electro-optic gate is based on radio-frequency transmission strip-line carrying the electric signal. A discontinuity in this strip-line occurs which become conductive, thanks to the optical command provided by the clock, due to a photo-conductive material. Semiconductor alloys from the III-V groups are widely used thanks to the high mobility of the photo-generated carriers allowing a high “on” state. In particular, GaAs present a good “off” state due to its band-gap energy. However, this restrains the optical clock wavelength explaining the use of optical sources around 800 nm.In this thesis, the focus was made on using mode-locked lasers in the Telecom range, thus using the improvement made on these sources during the past decades, while keeping GaAs as the active material in the electro-optic sampler. This is made possible by exalting the efficiency of two-photon absorption, which is usually weak in common structures. The approach followed here is to use a photonic crystal cavity. Thanks to its high optical mode confinement, non-linear absorption becomes efficient enough to generated carriers to modify the resistivity of the material. In addition, the nano-structuration of the material reduce tremendously the carrier lifetime, owing to switch from an “on” to “off” state fast enough to sample high frequency signals.The same function has been studied in the case where the signal is not carried electrically but optically. The all-optical gate function is realized using two photonic crystal resonators coupled together. The carrier generation by two-photon absorption induces a spectral shift of the resonance, used to modulate the transmission of the device. A fast all-optical gate, enabling signal processing up to 50 GHz is demonstrated here. The gate only requires a control power of about 200 fJ per pulses, which is low enough to use integrated optical sources (laser diodes) and, thanks to the small footprint, be easily integrated
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Archer, Cynthia. "A framework for representing non-stationary data with mixtures of linear models /." Full text open access at:, 2002. http://content.ohsu.edu/u?/etd,585.

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Åström, Freddie. "A Variational Approach to Image Diffusion in Non-Linear Domains." Licentiate thesis, Linköpings universitet, Datorseende, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-92788.

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Image filtering methods are designed to enhance noisy images captured in situations that are problematic for the camera sensor. Such noisy images originate from unfavourable illumination conditions, camera motion, or the desire to use only a low dose of ionising radiation in medical imaging. Therefore, in this thesis work I have investigated the theory of partial differential equations (PDE) to design filtering methods that attempt to remove noise from images. This is achieved by modeling and deriving energy functionals which in turn are minimized to attain a state of minimum energy. This state is obtained by solving the so called Euler-Lagrange equation. An important theoretical contribution of this work is that conditions are put forward determining when a PDE has a corresponding energy functional. This is in particular described in the case of the structure tensor, a commonly used tensor in computer vision.A primary component of this thesis work is to model adaptive image filtering such that any modification of the image is structure preserving, but yet is noise suppressing. In color image filtering this is a particular challenge since artifacts may be introduced at color discontinuities. For this purpose a non-Euclidian color opponent transformation has been analysed and used to separate the standard RGB color space into uncorrelated components.A common approach to achieve adaptive image filtering is to select an edge stopping function from a set of functions that have proven to work well in the past. The purpose of the edge stopping function is to inhibit smoothing of image features that are desired to be retained, such as lines, edges or other application dependent characteristics. Thus, a step from ad-hoc filtering based on experience towards an application-driven filtering is taken, such that only desired image features are processed. This improves what is characterised as visually relevant features, a topic which this thesis covers, in particular for medical imaging.The notion of what are relevant features is a subjective measure may be different from a layman's opinion compared to a professional's. Therefore, we advocate that any image filtering method should yield an improvement not only in numerical measures but also a visual improvement should be experienced by the respective end-user
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Fotinopoulos, Ioannis. "Root moments : a non-linear transformation technique with applications in signal processing." Thesis, Imperial College London, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.396276.

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Lynch, Michael Richard. "Adaptive techniques in signal processing and connectionist models." Thesis, University of Cambridge, 1990. https://www.repository.cam.ac.uk/handle/1810/244884.

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This thesis covers the development of a series of new methods and the application of adaptive filter theory which are combined to produce a generalised adaptive filter system which may be used to perform such tasks as pattern recognition. Firstly, the relevant background adaptive filter theory is discussed in Chapter 1 and methods and results which are important to the rest of the thesis are derived or referenced. Chapter 2 of this thesis covers the development of a new adaptive algorithm which is designed to give faster convergence than the LMS algorithm but unlike the Recursive Least Squares family of algorithms it does not require storage of a matrix with n2 elements, where n is the number of filter taps. In Chapter 3 a new extension of the LMS adaptive notch filter is derived and applied which gives an adaptive notch filter the ability to lock and track signals of varying pitch without sacrificing notch depth. This application of the LMS filter is of interest as it demonstrates a time varying filter solution to a stationary problem. The LMS filter is next extended to the multidimensional case which allows the application of LMS filters to image processing. The multidimensional filter is then applied to the problem of image registration and this new application of the LMS filter is shown to have significant advantages over current image registration methods. A consideration of the multidimensional LMS filter as a template matcher and pattern recogniser is given. In Chapter 5 a brief review of statistical pattern recognition is given, and in Chapter 6 a review of relevant connectionist models. In Chapter 7 the generalised adaptive filter is derived. This is an adaptive filter with the ability to model non-linear input-output relationships. The Volterra functional analysis of non-linear systems is given and this is combined with adaptive filter methods to give a generalised non-linear adaptive digital filter. This filter is then considered as a linear adaptive filter operating in a non-linearly extended vector space. This new filter is shown to have desirable properties as a pattern recognition system. The performance and properties of the new filter is compared with current connectionist models and results demonstrated in Chapter 8. In Chapter 9 further mathematical analysis of the networks leads to suggested methods to greatly reduce network complexity for a given problem by choosing suitable pattern classification indices and allowing it to define its own internal structure. In Chapter 10 robustness of the network to imperfections in its implementation is considered. Chapter 11 finishes the thesis with some conclusions and suggestions for future work.
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Kulakcherla, Sudheer. "Non [sic] linear adaptive filters for echo cancellation of speech coded signals /." free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p1426079.

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Hussain, A. "Novel artificial neural network architectures and algorithms for non-linear dynamical system modelling and digital communications applications." Thesis, University of Strathclyde, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263481.

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Turnes, Christopher Kowalczyk. "Efficient solutions to Toeplitz-structured linear systems for signal processing." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51878.

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This research develops efficient solution methods for linear systems with scalar and multi-level Toeplitz structure. Toeplitz systems are common in one-dimensional signal-processing applications, and typically correspond to temporal- or spatial-invariance in the underlying physical phenomenon. Over time, a number of algorithms have been developed to solve these systems economically by exploiting their structure. These developments began with the Levinson-Durbin recursion, a classical fast method for solving Toeplitz systems that has become a standard algorithm in signal processing. Over time, more advanced routines known as superfast algorithms were introduced that are capable of solving Toeplitz systems with even lower asymptotic complexity. For multi-dimensional signals, temporally- and spatially-invariant systems have linear-algebraic descriptions characterized by multi-level Toeplitz matrices, which exhibit Toeplitz structure on multiple levels. These matrices lack the same algebraic properties and structural simplicity of their scalar analogs. As a result, it has proven exceedingly difficult to extend the existing scalar Toeplitz algorithms for their treatment. This research presents algorithms to solve scalar and two-level Toeplitz systems through a constructive approach, using methods devised for specialized cases to build more general solution methods. These methods extend known scalar Toeplitz inversion results to more general scalar least-squares problems and to multi-level Toeplitz problems. The resulting algorithms have the potential to provide substantial computational gains for a large class of problems in signal processing, such as image deconvolution, non-uniform resampling, and the reconstruction of spatial volumes from non-uniform Fourier samples.
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Books on the topic "NON-LINEAR SIGNAL PROCESSING"

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Holambe, Raghunath S. Advances in Non-Linear Modeling for Speech Processing. Boston, MA: Springer US, 2012.

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1958-, Marshall Stephen, Harvey Neal 1966-, and Shah Druti 1966-, eds. Noblesse Workshop on Non-linear Model Based Image Analysis: Proceedings, NMBIA, 1-3 July 1998, Glasgow. London: Springer, 1998.

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Castanié, Francis. Non-Linear Signal Processing. Wiley & Sons, Incorporated, John, 2016.

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Castanié, Francis. Non-Linear Signal Processing. Wiley & Sons, Incorporated, John, 2016.

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Castanié, Francis. Non-Linear Signal Processing. Wiley & Sons, Incorporated, John, 2016.

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Castanié, Francis. Non-Linear Signal Processing. Wiley & Sons, Incorporated, John, 2016.

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Bugnon, Francois J. Team differential games and non-linear signal processing. 1986.

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Marshall, Stephen, Noblesse Workshop on Non-Linear Model Based Image Analysis, Neal Harvey, and Druti Shah. Noblesse Workshop on Non-Linear Model Based Image Analysis: Proceedings of Nmbia, 1-3 July 1998, Glasgow. Springer-Verlag Telos, 1999.

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Wendling, Fabrice, Marco Congendo, and Fernando H. Lopes da Silva. EEG Analysis. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0044.

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This chapter addresses the analysis and quantification of electroencephalographic (EEG) and magnetoencephalographic (MEG) signals. Topics include characteristics of these signals and practical issues such as sampling, filtering, and artifact rejection. Basic concepts of analysis in time and frequency domains are presented, with attention to non-stationary signals focusing on time-frequency signal decomposition, analytic signal and Hilbert transform, wavelet transform, matching pursuit, blind source separation and independent component analysis, canonical correlation analysis, and empirical model decomposition. The behavior of these methods in denoising EEG signals is illustrated. Concepts of functional and effective connectivity are developed with emphasis on methods to estimate causality and phase and time delays using linear and nonlinear methods. Attention is given to Granger causality and methods inspired by this concept. A concrete example is provided to show how information processing methods can be combined in the detection and classification of transient events in EEG/MEG signals.
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Holland, John H. 6. Emergence. Oxford University Press, 2014. http://dx.doi.org/10.1093/actrade/9780199662548.003.0006.

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‘Emergence’ looks at the relations between building blocks, generated systems, and the phenomenon of emergence. To understand emergent phenomena, it is necessary to describe the emergence of a system’s behaviour from the non-additive interactions of its building blocks. Emergence occurs when the generators for a generated system combine to yield objects having properties not obtained by summing properties of the individual generators. Co-evolution, often mediated by tags, is one of the major mechanisms for generating non-linear interactions between CAS agents. Tags serve as building blocks but can also be constructed from other building blocks. Tag recombination provides a general mechanism for emergence, because signal-processing lies at the heart of all complex systems.
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Book chapters on the topic "NON-LINEAR SIGNAL PROCESSING"

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Padmanabhan, Tattamangalam R. "Non-linear Signal Processing." In Industrial Instrumentation, 157–95. London: Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0451-3_6.

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Chonavel, Thierry. "Non-linear Transforms of Processes." In Statistical Signal Processing, 69–78. London: Springer London, 2002. http://dx.doi.org/10.1007/978-1-4471-0139-0_7.

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Karrenberg, Ulrich. "Linear and non-linear processes." In An Interactive Multimedia Introduction to Signal Processing, 175–216. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04949-5_8.

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Gupta, Kavya, and Angshul Majumdar. "Greedy Algorithms for Non-linear Sparse Recovery." In Machine Intelligence and Signal Processing, 99–108. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2625-3_9.

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Mohler, R. R., and W. J. Kolodziej. "Conditionally Linear and Non-Gaussian Processes." In Topics in Non-Gaussian Signal Processing, 58–72. New York, NY: Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4613-8859-3_4.

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Dickman, Arie. "Non-Linear and Batch Filters." In Verified Signal Processing Algorithms in Matlab and C, 89–93. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93363-0_6.

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Nigmatullin, Raoul R., Paolo Lino, and Guido Maione. "The Eigen-Coordinates Method: Reduction of Non-linear Fitting Problems." In New Digital Signal Processing Methods, 1–48. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45359-6_1.

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Kulhavý, Rudolf. "Recursive Nonlinear Estimation of Non-linear/Non-Gaussian Dynamic Models." In Computer Intensive Methods in Control and Signal Processing, 141–67. Boston, MA: Birkhäuser Boston, 1997. http://dx.doi.org/10.1007/978-1-4612-1996-5_8.

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Minelly, S., A. Curley, P. Giaccone, and G. A. Jones. "Multi-Channel Adaptive Signal Processing of Colour Cinematographic Imagery." In Noblesse Workshop on Non-Linear Model Based Image Analysis, 193–98. London: Springer London, 1998. http://dx.doi.org/10.1007/978-1-4471-1597-7_31.

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Sheng, Hu, YangQuan Chen, and TianShuang Qiu. "Non-linear Transform Based Robust Adaptive Latency Change Estimation of Evoked Potentials." In Fractional Processes and Fractional-Order Signal Processing, 233–42. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2233-3_12.

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Conference papers on the topic "NON-LINEAR SIGNAL PROCESSING"

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Fitzgerald, W. J., R. L. Smith, A. T. Walden, and P. C. Young. "Nonlinear and nonstationary signal processing." In IEE Colloquium on Non-Linear Signal and Image Processing. IEE, 1998. http://dx.doi.org/10.1049/ic:19980449.

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Arthur, N., and J. Penman. "Condition monitoring with non-linear signal processing." In IEE Colloquium on Non-Linear Signal and Image Processing. IEE, 1998. http://dx.doi.org/10.1049/ic:19980439.

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Macleod, M. D. "Two applications of simple non-linear signal processing." In IEE Colloquium on Non-Linear Signal and Image Processing. IEE, 1998. http://dx.doi.org/10.1049/ic:19980442.

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Fitzgerald, W. J. "The Bayesian approach to signal modelling." In IEE Colloquium on Non-Linear Signal and Image Processing. IEE, 1998. http://dx.doi.org/10.1049/ic:19980444.

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Healey, A. J., and S. Leeman. "A nonlinear processing technique for removing coherent interference artefacts." In IEE Colloquium on Non-Linear Signal and Image Processing. IEE, 1998. http://dx.doi.org/10.1049/ic:19980436.

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Woolfries, N., P. Lysaght, S. Marshall, G. McGregor, and D. Robinson. "Fast implementation of non-linear filters using FPGAs." In IEE Colloquium on Non-Linear Signal and Image Processing. IEE, 1998. http://dx.doi.org/10.1049/ic:19980448.

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Davies, E. R., M. Bateman, J. Chambers, and C. Ridgway. "Hybrid non-linear filters for locating speckled contaminants in grain." In IEE Colloquium on Non-Linear Signal and Image Processing. IEE, 1998. http://dx.doi.org/10.1049/ic:19980447.

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Li, Zhixiang, Yinlong Wang, Xiufeng Gao, Xiwu Wang, Qianjin Li, and Xi Li. "Non-linear signal processing with improved STAM algorithm." In 2014 2nd International Conference on Information Technology and Electronic Commerce (ICITEC). IEEE, 2014. http://dx.doi.org/10.1109/icitec.2014.7105603.

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Beaumont, J. M. "Morphological properties of rank ordering filters." In IEE Colloquium on Non-Linear Signal and Image Processing. IEE, 1998. http://dx.doi.org/10.1049/ic:19980437.

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Harvey, N. R., and S. Marshall. "Video and film restoration using mathematical morphology." In IEE Colloquium on Non-Linear Signal and Image Processing. IEE, 1998. http://dx.doi.org/10.1049/ic:19980438.

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Reports on the topic "NON-LINEAR SIGNAL PROCESSING"

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Cronin-Golomb, Mark, and Jed Khoury. Non-Linear Optical Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, August 1995. http://dx.doi.org/10.21236/ada407564.

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Dagenais, M. High Speed, Low Power Non-Linear Optical Signal Processing in Semiconductors. Fort Belvoir, VA: Defense Technical Information Center, June 1985. http://dx.doi.org/10.21236/ada159054.

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Hamlin, Alexandra, Erik Kobylarz, James Lever, Susan Taylor, and Laura Ray. Assessing the feasibility of detecting epileptic seizures using non-cerebral sensor. Engineer Research and Development Center (U.S.), December 2021. http://dx.doi.org/10.21079/11681/42562.

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This paper investigates the feasibility of using non-cerebral, time-series data to detect epileptic seizures. Data were recorded from fifteen patients (7 male, 5 female, 3 not noted, mean age 36.17 yrs), five of whom had a total of seven seizures. Patients were monitored in an inpatient setting using standard video electroencephalography (vEEG), while also wearing sensors monitoring electrocardiography, electrodermal activity, electromyography, accelerometry, and audio signals (vocalizations). A systematic and detailed study was conducted to identify the sensors and the features derived from the non-cerebral sensors that contribute most significantly to separability of data acquired during seizures from non-seizure data. Post-processing of the data using linear discriminant analysis (LDA) shows that seizure data are strongly separable from non-seizure data based on features derived from the signals recorded. The mean area under the receiver operator characteristic (ROC) curve for each individual patient that experienced a seizure during data collection, calculated using LDA, was 0.9682. The features that contribute most significantly to seizure detection differ for each patient. The results show that a multimodal approach to seizure detection using the specified sensor suite is promising in detecting seizures with both sensitivity and specificity. Moreover, the study provides a means to quantify the contribution of each sensor and feature to separability. Development of a non-electroencephalography (EEG) based seizure detection device would give doctors a more accurate seizure count outside of the clinical setting, improving treatment and the quality of life of epilepsy patients.
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Alchanatis, Victor, Stephen W. Searcy, Moshe Meron, W. Lee, G. Y. Li, and A. Ben Porath. Prediction of Nitrogen Stress Using Reflectance Techniques. United States Department of Agriculture, November 2001. http://dx.doi.org/10.32747/2001.7580664.bard.

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Commercial agriculture has come under increasing pressure to reduce nitrogen fertilizer inputs in order to minimize potential nonpoint source pollution of ground and surface waters. This has resulted in increased interest in site specific fertilizer management. One way to solve pollution problems would be to determine crop nutrient needs in real time, using remote detection, and regulating fertilizer dispensed by an applicator. By detecting actual plant needs, only the additional nitrogen necessary to optimize production would be supplied. This research aimed to develop techniques for real time assessment of nitrogen status of corn using a mobile sensor with the potential to regulate nitrogen application based on data from that sensor. Specifically, the research first attempted to determine the system parameters necessary to optimize reflectance spectra of corn plants as a function of growth stage, chlorophyll and nitrogen status. In addition to that, an adaptable, multispectral sensor and the signal processing algorithm to provide real time, in-field assessment of corn nitrogen status was developed. Spectral characteristics of corn leaves reflectance were investigated in order to estimate the nitrogen status of the plants, using a commercial laboratory spectrometer. Statistical models relating leaf N and reflectance spectra were developed for both greenhouse and field plots. A basis was established for assessing nitrogen status using spectral reflectance from plant canopies. The combined effect of variety and N treatment was studied by measuring the reflectance of three varieties of different leaf characteristic color and five different N treatments. The variety effect on the reflectance at 552 nm was not significant (a = 0.01), while canonical discriminant analysis showed promising results for distinguishing different variety and N treatment, using spectral reflectance. Ambient illumination was found inappropriate for reliable, one-beam spectral reflectance measurement of the plants canopy due to the strong spectral lines of sunlight. Therefore, artificial light was consequently used. For in-field N status measurement, a dark chamber was constructed, to include the sensor, along with artificial illumination. Two different approaches were tested (i) use of spatially scattered artificial light, and (ii) use of collimated artificial light beam. It was found that the collimated beam along with a proper design of the sensor-beam geometry yielded the best results in terms of reducing the noise due to variable background, and maintaining the same distance from the sensor to the sample point of the canopy. A multispectral sensor assembly, based on a linear variable filter was designed, constructed and tested. The sensor assembly combined two sensors to cover the range of 400 to 1100 nm, a mounting frame, and a field data acquisition system. Using the mobile dark chamber and the developed sensor, as well as an off-the-shelf sensor, in- field nitrogen status of the plants canopy was measured. Statistical analysis of the acquired in-field data showed that the nitrogen status of the com leaves can be predicted with a SEP (Standard Error of Prediction) of 0.27%. The stage of maturity of the crop affected the relationship between the reflectance spectrum and the nitrogen status of the leaves. Specifically, the best prediction results were obtained when a separate model was used for each maturity stage. In-field assessment of the nitrogen status of corn leaves was successfully carried out by non contact measurement of the reflectance spectrum. This technology is now mature to be incorporated in field implements for on-line control of fertilizer application.
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