1,530 research outputs found
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Review of Unbiased FIR Filters, Smoothers, and Predictors for Polynomial Signals
Extracting an estimate of a slowly varying signal corrupted by noise is a common task. Examples can be found in industrial, scientific and biomedical instrumentation. Depending on the nature of the application the signal estimate is allowed to be a delayed estimate of the original signal or, in the other extreme, no delay is tolerated. These cases are commonly referred to as filtering, prediction, and smoothing depending on the amount of advance or lag between the input data set and the output data set. In this review paper we provide a comprehensive set of design and analysis tools for designing unbiased FIR filters, predictors, and smoothers for slowly varying signals, i.e. signals that can be modeled by low order polynomials. Explicit expressions of parameters needed in practical implementations are given. Real life examples are provided including cases where the method is extended to signals that are piecewise slowly varying. A critical view on recursive implementations of the algorithms is provided
Multi-Level Pre-Correlation RFI Flagging for Real-Time Implementation on UniBoard
Because of the denser active use of the spectrum, and because of radio
telescopes higher sensitivity, radio frequency interference (RFI) mitigation
has become a sensitive topic for current and future radio telescope designs.
Even if quite sophisticated approaches have been proposed in the recent years,
the majority of RFI mitigation operational procedures are based on
post-correlation corrupted data flagging. Moreover, given the huge amount of
data delivered by current and next generation radio telescopes, all these RFI
detection procedures have to be at least automatic and, if possible, real-time.
In this paper, the implementation of a real-time pre-correlation RFI
detection and flagging procedure into generic high-performance computing
platforms based on Field Programmable Gate Arrays (FPGA) is described,
simulated and tested. One of these boards, UniBoard, developed under a Joint
Research Activity in the RadioNet FP7 European programme is based on eight
FPGAs interconnected by a high speed transceiver mesh. It provides up to ~4
TMACs with Altera Stratix IV FPGA and 160 Gbps data rate for the input data
stream.
Considering the high in-out data rate in the pre-correlation stages, only
real-time and go-through detectors (i.e. no iterative processing) can be
implemented. In this paper, a real-time and adaptive detection scheme is
described.
An ongoing case study has been set up with the Electronic Multi-Beam Radio
Astronomy Concept (EMBRACE) radio telescope facility at Nan\c{c}ay Observatory.
The objective is to evaluate the performances of this concept in term of
hardware complexity, detection efficiency and additional RFI metadata rate
cost. The UniBoard implementation scheme is described.Comment: 16 pages, 13 figure
An efficient of estimation stages for segmentation skin lesions based optimization algorithm
Modern dermatology distinguishes premature diagnosis for example an important part in reducing the death percentage and promising less aggressive treatment for patients. The classifications comprise various stages that must be selected suitably using the characteristics of the filter pointing to get a dependable analysis. The dermoscopic images hold challenges to be faced and overcome to enhance the automatic diagnosis of hazardous lesions. It is calculated to survey a different metaheuristic and evolutionary computing working for filter design systems. Approximately general computing techniques are observed to improve features of infect design method. Nevertheless, the median filter (MF) is normally multimodal with respect to the filter factors and so, reliable approaches that can provide optimal solutions are required. The design of MF depends on modern artificial swarm intelligence technique (MASIT) optimization algorithm which has proven to be more effective than other population-based algorithms to improve of estimation stages for segmentation skin lesions. A controlled artificial bee colony (ABC) algorithm is advanced for solving factors optimization problems and, also the physical-programming-depend on ABC way is applied to proposal median filter, and the outcomes are compared to another approaches
Chaotic multi-objective optimization based design of fractional order PI{\lambda}D{\mu} controller in AVR system
In this paper, a fractional order (FO) PI{\lambda}D\mu controller is designed
to take care of various contradictory objective functions for an Automatic
Voltage Regulator (AVR) system. An improved evolutionary Non-dominated Sorting
Genetic Algorithm II (NSGA II), which is augmented with a chaotic map for
greater effectiveness, is used for the multi-objective optimization problem.
The Pareto fronts showing the trade-off between different design criteria are
obtained for the PI{\lambda}D\mu and PID controller. A comparative analysis is
done with respect to the standard PID controller to demonstrate the merits and
demerits of the fractional order PI{\lambda}D\mu controller.Comment: 30 pages, 14 figure
Data Acquisition, Triggering, and Filtering at the Auger Engineering Radio Array
The Auger Engineering Radio Array (AERA) is currently detecting cosmic rays
of energies at and above 10^17 eV at the Pierre Auger Observatory, by
triggering on the radio emission produced in the associated air showers. The
radio-detection technique must cope with a significant background of man-made
radio-frequency interference, but can provide information on shower development
with a high duty cycle. We discuss our techniques to handle the challenges of
self-triggered radio detection in a low-power autonomous array, including
triggering and filtering algorithms, data acquisition design, and communication
systems.Comment: Contribution to VLVnT 2011, to be published in NIM A, 4 pages, 6
figure
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Adaptive spatial-temporal filtering applied to x-ray fluoroscopy angiography
Adaptive filtering of temporally varying X-ray image sequences acquired during endovascular interventions can improve the visual tracking of catheters by radiologists. Existing techniques blur the important parts of image sequences, such as catheter tips, anatomical structures and organs; and they may introduce trailing artifacts. To address this concern, an adaptive filtering process is presented to apply temporal filtering in regions without motion and spatial filtering in regions with motion. The adaptive filtering process is a multi-step procedure. First a normalized motion mask that describes the differences between two successive frames is generated. Secondly each frame is spatially filtered using the specific motion mask to specify different types of filtering in each region. Third an IIR filter is then used to combine the spatially filtered image with the previous output image; the motion mask thus serves as a weighted input mask to determine how much spatial and temporal filtering should be applied. This method results in improving both the stationary and moving fields. The visibility of static anatomical structures and organs increases, while the motion of the catheter tip and motion of anatomical structures and organs remain unblurred and visible during interventional procedures
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