Log in

Relevant bibliographies by topics / NON-LINEAR SIGNAL PROCESSING

Contents

Journal articles

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

Author: Grafiati

Published: 11 September 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'NON-LINEAR SIGNAL PROCESSING.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

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

1

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

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

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.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

3

Lunner, Thomas, Johan Hellgren, Stig Arlinger, and Claus Elberling. "Non-Linear Signal Processing in Digital Hearing Aids." Scandinavian Audiology 27, no. 4 (1998): 40–49. http://dx.doi.org/10.1080/010503998420649.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

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 (2013): 46–59. http://dx.doi.org/10.4018/ijmtie.2013070104.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

5

Adithya valli, N., and Dr D. Elizabath Rani. "Modified PWNLFM Signal for Side-Lobe Reduction." International Journal of Engineering & Technology 7, no. 4.20 (2018): 4. http://dx.doi.org/10.14419/ijet.v7i4.20.22110.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

6

BILLINGS, S. A., and Q. H. TAO. "Model validity tests for non-linear signal processing applications." International Journal of Control 54, no. 1 (1991): 157–94. http://dx.doi.org/10.1080/00207179108934155.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

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

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

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.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

9

Bilgehan, Bülent. "Efficient approximation for linear and non‐linear signal representation." IET Signal Processing 9, no. 3 (2015): 260–66. http://dx.doi.org/10.1049/iet-spr.2014.0070.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

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 (2018): 149. http://dx.doi.org/10.11591/ijict.v7i3.pp149-156.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

More sources

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!