Search results for "telecommunications"
showing 10 items of 1639 documents
Particle Group Metropolis Methods for Tracking the Leaf Area Index
2020
Monte Carlo (MC) algorithms are widely used for Bayesian inference in statistics, signal processing, and machine learning. In this work, we introduce an Markov Chain Monte Carlo (MCMC) technique driven by a particle filter. The resulting scheme is a generalization of the so-called Particle Metropolis-Hastings (PMH) method, where a suitable Markov chain of sets of weighted samples is generated. We also introduce a marginal version for the goal of jointly inferring dynamic and static variables. The proposed algorithms outperform the corresponding standard PMH schemes, as shown by numerical experiments.
Cell-average WENO with progressive order of accuracy close to discontinuities with applications to signal processing
2020
In this paper we translate to the cell-average setting the algorithm for the point-value discretization presented in S. Amat, J. Ruiz, C.-W. Shu, D. F. Y\'a\~nez, A new WENO-2r algorithm with progressive order of accuracy close to discontinuities, submitted to SIAM J. Numer. Anal.. This new strategy tries to improve the results of WENO-($2r-1$) algorithm close to the singularities, resulting in an optimal order of accuracy at these zones. The main idea is to modify the optimal weights so that they have a nonlinear expression that depends on the position of the discontinuities. In this paper we study the application of the new algorithm to signal processing using Harten's multiresolution. Se…
Blind multi-user detection by fast fixed point algorithm without prior knowledge of symbol-level timing
2003
We consider the estimation of the source process of the desired user an the downlink of a code-division multiple access (CDMA) communication system. In downlink signal processing, only the code of the mobile telephone user is known, while the codes of the interfering users are unknown. Blind source separation or independent component analysis is an approach offering the solution to this problem. In this work we apply the fast fixed point algorithm to the separation problem. The algorithm is based on fourth-order statistics optimization. Knowledge about the symbol level timing has to be known only coarsely.
PHASER – A Phase-Shifting Antenna for Low-Power Directional Communication
2017
This paper describes the design and empirical evaluation of PHASER — a mote prototype for low-power directional communication in wireless sensor networks. PHASER has a modular design that includes three components: a low-power radio, an RF signal processing chip, and two off-the-shelf antennas. Directional communication is achieved by splitting the output signal from the low-power radio chip and controlling programmatically the phase of each signal as it transmitted to each antenna. The net effect of controlling the phase of the signals is that they generate patterns of constructive and destructive interference as signals propagate. PHASER is well-suited for wireless sensor networks as it d…
Spectrum cartography using adaptive radial basis functions: Experimental validation
2017
In this paper, we experimentally validate the functionality of a developed algorithm for spectrum cartography using adaptive Gaussian radial basis functions (RBF). The RBF are strategically centered around representative centroid locations in a machine learning context. We assume no prior knowledge about neither the power spectral densities (PSD) of the transmitters nor their locations. Instead, the received signal power at each location is estimated as a linear combination of different RBFs. The weights of the RBFs, their Gaussian decaying parameters and locations are jointly optimized using expectation maximization with a least squares loss function and a quadratic regularizer. The perfor…
Efficient Analysis and Synthesis Using a New Factorization of the Gabor Frame Matrix
2018
In this paper, we consider the case in which one needs to carry out Gabor analysis and synthesis on large signals using a short support analysis window and its corresponding, possibly longer canonical dual window, respectively. In this asymmetric context, we propose a novel factorization of the Gabor frame operator that exploits its strong and well-known structure and leads to a computational cost for synthesis, which is comparable to the one needed for short support analysis. The proposed factorization applies to any Gabor system with very mild conditions and leads to a potentially promising alternative to current synthesis algorithms in the case of short analysis windows whose support is …
Route diversity analyses for free-space optical wireless links within turbulent scenarios
2013
Free-Space Optical (FSO) communications link performance is highly affected when propagating through the time-spatially variable turbulent environment. In order to improve signal reception, several mitigation techniques have been proposed and analytically investigated. This paper presents experimental results for the route diversity technique evaluations for a specific case when several diversity links intersects a common turbulent area and concurrently each passing regions with different turbulence flows.
Photonic fractional Fourier transformer with a single dispersive device
2013
In this work we used the temporal analog of spatial Fresnel diffraction to design a temporal fractional Fourier transformer with a single dispersive device, in this way avoiding the use of quadratic phase modulators. We demonstrate that a single dispersive passive device inherently provides the fractional Fourier transform of an incident optical pulse. The relationships linking the fractional Fourier transform order and scaling factor with the dispersion parameters are derived. We first provide some numerical results in order to prove the validity of our proposal, using a fiber Bragg grating as the dispersive device. Next, we experimentally demonstrate the feasibility of this proposal by us…
Design of Asymmetric Shift Operators for Efficient Decentralized Subspace Projection
2021
A large number of applications in decentralized signal processing includes projecting a vector of noisy observations onto a subspace dictated by prior information about the field being monitored. Accomplishing such a task in a centralized fashion in networks is prone to a number of issues such as large power consumption, congestion at certain nodes and suffers from robustness issues against possible node failures. Decentralized subspace projection is an alternative method to address those issues. Recently, it has been shown that graph filters (GFs) can be implemented to perform decentralized subspace projection. However, most of the existing methods have focused on designing GFs for symmetr…
Information – theoretic characterization of concurrent activity of neural spike trains
2021
The analysis of massively parallel spike train recordings facilitates investigation of communications and synchronization in neural networks. In this work we develop and evaluate a measure of concurrent neural activity, which is based on intrinsic firing properties of the recorded neural units. An overall single neuron activity is unfolded in time and decomposed into working and non-firing state, providing a coarse, binary representation of the neurons functional state. We propose a modified measure of mutual information to reflect the degree of simultaneous activation and concurrency in neural firing patterns. The measure is shown to be sensitive to both correlations and anti-correlations,…