Search results for "signal processing"
showing 10 items of 2451 documents
Detailed quantum-chromodynamic predictions for high-pTprocesses
1978
High-${p}_{T}$ single-particle inclusive cross section calculations are presented for the CERN ISR and ISABELLE energy ranges, taking into account all lowest-order hard-scattering subprocesses required by quantum chromodynamics (QCD). The input quark and gluon distribution and fragmentation functions were determined from analyses of deep-inelastic lepton data and were subject to various theoretical constraints such as sum rules and SU(3) symmetry. We thoroughly discuss the effects of the individual contributions from fermionic and gluonic subprocesses, as well as those effects stemming from QCD scaling violations in parton distributions and/or fragmentation functions. In particular, the inc…
Wavelet analysis and neural network classifiers to detect mid-sagittal sections for nuchal translucency measurement
2016
We propose a methodology to support the physician in the automatic identification of mid-sagittal sections of the fetus in ultrasound videos acquired during the first trimester of pregnancy. A good mid-sagittal section is a key requirement to make the correct measurement of nuchal translucency which is one of the main marker for screening of chromosomal defects such as trisomy 13, 18 and 21. NT measurement is beyond the scope of this article. The proposed methodology is mainly based on wavelet analysis and neural network classifiers to detect the jawbone and on radial symmetry analysis to detect the choroid plexus. Those steps allow to identify the frames which represent correct mid-sagitta…
Generalization of Canny–Deriche filter for detection of noisy exponential edge
2002
This paper presents a generalization of the Canny-Deriche filter for ramp edge detection with optimization criteria used by Canny (signal-to-noise ratio, localization, and suppression of false responses). Using techniques similar to those developed by Deriche, we derive a filter which maximizes the product of the first two criteria under the constraint of the last one. The result is an infinite length impulse response filter which leads to a stable third-order recursive implementation. Its performance shows an increase of the signal-to-noise ratio in the case of blurred and noisy images, compared to the results obtained from Deriche's filter.
Objectivization of the electrical discharge measurement results taken by the acoustic emission method
2006
The subject matter of this paper refers to the improvement of the acoustic emission method (AE) in its application for diagnostics of insulation systems of power appliances whereas the detailed subject matter is connected with determining the possibilities and indicating the range of using statistical and digital methods of signal processing for the evaluation of the AE pulses generated by partial discharges (PDs), which can occur in paper-oil insulation of power transformers.
Generation of Hardware/Software systems based on CAL dataflow description
2011
International audience; This paper presents a new development of rapid prototyping tools for system design based on data-flow specifications. In this context, the efficiency of tools for the automatic translation from the data-flow programs to C and/or HDL are assessed by means of two design cases. The paper also introduces the new concept of the automatic synthesis of interfaces. Such generic interfaces are implemented by using an embedded microprocessor, which can support a large variety of interfaces already available as native IP libraries in the case of FPGA. The two design cases described here have been developed, tested and validated on different implementation platforms. The results…
Stackelberg Game Theory Based Energy Management Systems in the Presence of Renewable Energy Sources
2021
The game theory concept has been adapted for energy management between energy producers and consumers in the presence of renewable energy sources (RES) and electric vehicles (EVs). The objective of...
Non-linear RLS-based algorithm for pattern classification
2006
A new non-linear recursive least squares (RLS) algorithm is presented in the context of pattern classification problems. The algorithm incorporates the non-linearity of the filter's output in the updating rules of the classical RLS algorithm. The proposed method yields lower stationary error levels when compared to the standard LMS and RLS algorithms in a classical application of pattern classification, such as the channel equalization problem.
Graph recursive least squares filter for topology inference in causal data processes
2017
In this paper, we introduce the concept of recursive least squares graph filters for online topology inference in data networks that are modelled as Causal Graph Processes (CGP). A Causal Graph Process (CGP) is an auto regressive process in the time series associated to different variables, and whose coefficients are the so-called graph filters, which are matrix polynomials with different orders of the graph adjacency matrix. Given the time series of data at different variables, the goal is to estimate these graph filters, hence the associated underlying adjacency matrix. Previously proposed algorithms have focused on a batch approach, assuming implicitly stationarity of the CGP. We propose…
Wavelet correlation filter for wide-angle seismic data
2002
A new filtering technique for single-fold wide-angle reflection/refraction seismic data is presented. The technique is based on the wavelet decomposition of a set of adjacent traces followed by coherence analysis. The filtering procedure consists of three steps. In the first, a wavelet decomposition of traces into different detail levels is performed. In the second, the coherence attributes for each level are evaluated by calculating cross-correlation functions of detail portions contained in a space–time moving window. Finally, the filtered traces are obtained as a weighted reconstruction of the trace details. Each weight is obtained from the coherence-attributes distribution estimated in …
Compartmental analysis of dynamic nuclear medicine data: Models and identifiability
2016
Compartmental models based on tracer mass balance are extensively used in clinical and pre-clinical nuclear medicine in order to obtain quantitative information on tracer metabolism in the biological tissue. This paper is the first of a series of two that deal with the problem of tracer coefficient estimation via compartmental modelling in an inverse problem framework. Specifically, here we discuss the identifiability problem for a general n-dimension compartmental system and provide uniqueness results in the case of two-compartment and three-compartment compartmental models. The second paper will utilize this framework in order to show how non-linear regularization schemes can be applied t…