Search results for "Signal processing"
showing 10 items of 2451 documents
Some experimental issues of AFM tip blind estimation. The effect of noise and resolution
2006
The convolution of tip shape on sample topography can introduce significant inaccuracy in an AFM image, when the tip radius is comparable to the typical dimension of the sample features to be observed. The blind estimation method allows one to obtain information on the AFM tip through an unknown characterizer sample and thus to perform the deconvolution of the tip shape from an image. When applying the blind estimation method to determine the AFM tip shape, some apparently trivial issues relating to the experimental operating parameters must be taken into account. In this paper, the effects of the operating parameters, e.g., sampling intervals (resolution) and instrumental noise, have been …
Mutual-information based rate-adaptation for Multi-User TH-IR-UWB coded system
2011
In this paper we present a coding rate adaptation technique for a Time-Hopping Impulse-Radio Ultra-Wide Band (TH-IR-UWB) system assuming that the Multi-User Interference (MUI) is modeled as an additive interference noise following a Generalized Gaussian Distribution (GGD). The shape parameter induced by the GGD model is in general time-variant since it strongly depends on the essential UWB system parameters and the received signal power of the active users. In this paper, we show that the performance of a TH-IR-UWB LDPC coded system is quite independent of the GGD shape parameter when we consider the mutual information between the soft input to the decoder and the transmitted sequence, espe…
Signal-to-noise ratio in reproducing kernel Hilbert spaces
2018
This paper introduces the kernel signal-to-noise ratio (kSNR) for different machine learning and signal processing applications}. The kSNR seeks to maximize the signal variance while minimizing the estimated noise variance explicitly in a reproducing kernel Hilbert space (rkHs). The kSNR gives rise to considering complex signal-to-noise relations beyond additive noise models, and can be seen as a useful signal-to-noise regularizer for feature extraction and dimensionality reduction. We show that the kSNR generalizes kernel PCA (and other spectral dimensionality reduction methods), least squares SVM, and kernel ridge regression to deal with cases where signal and noise cannot be assumed inde…
HF Noise Measurements Based on Software Defined Radio Dual Receiver and Two Orthogonal Inverted Vee Antennas
2020
Increasing the data transfer rate in the High Frequency (HF) range involves enlarging the bandwidth of the channel from the standard value of 3 kHz to values of 6, 12, 24, 48 and even 96 kHz. Real-time evaluation of the noise power in the channel under such conditions is essential. This paper aims to implement an automated system for real-time measurement of noise in the HF range. It is composed of two Software Defined Radio (SDR) synchronized receivers and two orthogonal Inverted Vee antennas. Testing the system demonstrates its ability to distinguish between noise and signals generated as a result of human activity. Preliminary results of measurements performed in an urban location are co…
Impulse noise removal on an embedded, low memory SIMD processor
2003
Vector median filters efficiently reduce noise while preserving image details. However, their high computational complexity for color images makes them impractical for real-time systems. We propose new computationally efficient filtering algorithms, called index mapping filters (IMF). These filtering algorithms are accelerated by implementing them on a massively data parallel processor array. In addition to greater computational efficiency, these algorithms result in robust noise reduction of corrupted color images. Analyses of mean square error, signal-to-noise-ratio, and visual comparison metrics indicate that IMF are competitive with the vector median filter (VMF) in their ability to cor…
Robust adaptive algorithm with low computational cost
2006
An adaptive algorithm, which is robust to impulsive noise, is proposed. The cost function underlying this algorithm contains a parameter that controls the immunity to impulsive noise and can be easily adapted. Moreover, weight updating involves a nonlinear function, which recently has been shown to have an efficient hardware implementation. The proposed adaptive algorithm has been successfully tested in terms of accuracy and convergence on a system-identification simulation.
Discrete wavelet transform implementation in Fourier domain for multidimensional signal
2002
Wavelet transforms are often calculated by using the Mallat algorithm. In this algorithm, a signal is decomposed by a cascade of filtering and downsampling operations. Computing time can be important but the filtering operations can be speeded up by using fast Fourier transform (FFT)-based convolutions. Since it is necessary to work in the Fourier domain when large filters are used, we present some results of Fourier-based optimization of the sampling operations. Acceleration can be obtained by expressing the samplings in the Fourier domain. The general equations of the down- and upsampling of digital multidimensional signals are given. It is shown that for special cases such as the separab…
Vehicular Motion and Traffic Breakdown: Evaluation of Energy Balance
2009
Microscopic traffic models based on follow–the–leader behaviour are strongly asymmetrically interacting many–particle systems. The well–known Bando’s optimal velocity model includes the fact that (firstly) the driver is always looking forward interacting with the lead vehicle and (secondly) the car travels on the road always with friction. Due to these realistic assumptions the moving car needs petrol for the engine to compensate dissipation by rolling friction. We investigate the flux of mechanical energy to evaluate the energy balance out of the given nonlinear dynamical system of vehicular particles. In order to understand the traffic breakdown as transition from free flow to congested t…
Polarization attraction using counter-propagating waves in optical fiber at telecommunication wavelengths
2008
International audience; In this work, we report the experimental observation of a polarization attraction process which can occur in optical fibers at telecommunication wavelengths. More precisely, we have numerically and experimentally shown that a polarization attractor, based on the injection of two counter-propagating waves around 1.55 mu m into a 2-m long high nonlinear fiber, can transform any input polarization state into a unique well-defined output polarization state.
A Note on the Nonlinear Landweber Iteration
2014
We reconsider the Landweber iteration for nonlinear ill-posed problems. It is known that this method becomes a regularization method in the case when the iteration is terminated as soon as the residual drops below a certain multiple of the noise level in the data. So far, all known estimates of this factor are greater than two. Here we derive a smaller factor that may be arbitrarily close to one depending on the type of nonlinearity of the underlying operator equation.