signalprocessing software is characterized by a heavy emphasis on arithmetic calculations and the lack of complicated control structures, placing specific constraints on which testing techniques are applicable and ho...
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signalprocessing software is characterized by a heavy emphasis on arithmetic calculations and the lack of complicated control structures, placing specific constraints on which testing techniques are applicable and how signalprocessing software can be efficiently tested. In this paper, we analyze the unique characteristics of signalprocessing software from the testing viewpoint and propose applied techniques for tackling the verification challenges of such software. We propose a testing method for the signalprocessing context and provide examples of its application to an FIR and a second order IIR filter. This method extends the applicability of algebraic testing and domain testing methods to signalprocessing software. The developed method applies to linear systems and can be further extended to take nonlinearities in the tested system into account.
This paper investigates the benefits derived by adopting the use of Graphics processing Unit (GPU) parallel programming in the field of biomedical signalprocessing. The differences in execution time when computing th...
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This paper investigates the benefits derived by adopting the use of Graphics processing Unit (GPU) parallel programming in the field of biomedical signalprocessing. The differences in execution time when computing the Correlation Dimension (CD) of multivariate neurophysiological recordings and the Skin Conductance Level (SCL) are reported by comparing several common programming environments. Moreover, as indicated in this study, the combination of parallel programming with special design techniques dealing with memory management issues such as data transfer between device memory and GPU may further accelerate the processing speed. So, the minimization achieved in the time execution by means of proper parallel architecture design may reach a factor of 29 in comparison with pure C language. Therefore, the role of parallel GPU programming environment may be beneficial for numerous biomedical applications within the sphere of biosignalprocessing.
Wind power forecasting (WPF) has turned into a substantial tool for limiting the negative impact of wind power intermittency on power system. In this paper, we study and compare two different WPF algorithms: classical...
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Wind power forecasting (WPF) has turned into a substantial tool for limiting the negative impact of wind power intermittency on power system. In this paper, we study and compare two different WPF algorithms: classical autoregressive model (AR), as a base case method, and kernel density estimation (KDE) with minimum mean square error estimator (MMSE). Using the data history of a wind farm in Colorado, these two algorithms are implemented in MATLAB and used to produce 24 hours ahead predictions of wind power time series of the said wind farm. The results obtained from the two methods are then compared from various perspectives (precision, applicability, etc.). The comparisons show that although AR-based wind power prediction has slightly less error than KDE, AR-based prediction does not produce probability density function (PDF) of wind speed/power, while KDE does. PDF of wind speed/power is an important parameter for estimating the required reserve allocation in economic dispatch studies.
For airborne Earth observation applications, there is a special interest in lightweight, cost effective, imaging sensors of high resolution. The combination of frequency modulated continuous wave (FMCW) technology and...
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For airborne Earth observation applications, there is a special interest in lightweight, cost effective, imaging sensors of high resolution. The combination of frequency modulated continuous wave (FMCW) technology and synthetic aperture radar (SAR) techniques can lead to such a sensor. In this paper, a developed algorithm for SAR imaging that takes into account the special characteristics of FMCW signals is presented. Constrains for the validity of the stop and go approximation are shown. A demonstrator system has been built at Delft University of Technology and some results from the last airborne campaign are presented.
Adaptive signal processing algorithms are often used in order to "track" an unknown time-varying parameter vector. Such algorithms are typically some form of stochastic gradient-descent algorithm. The Widrow...
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Adaptive signal processing algorithms are often used in order to "track" an unknown time-varying parameter vector. Such algorithms are typically some form of stochastic gradient-descent algorithm. The Widrow LMS algorithm is apparently the most frequently used. This work develops an upper bound on the norm-squared error between the parameter vector being tracked and the value obtained by the algorithm. The upper bound illustrates the relationship between the algorithm step-size and the maximum rate of variation in the parameter vector. Finally, some simple covariance decay-rate conditions are imposed to obtain a bound on the mean square error.
Natural gas and carbon monoxide domestic detectors available in the market present serious deficiencies in terms of selectivity. Their problems result in a high percentage of false alarms. A possible solution of this ...
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Natural gas and carbon monoxide domestic detectors available in the market present serious deficiencies in terms of selectivity. Their problems result in a high percentage of false alarms. A possible solution of this problem is to improve the performance by means of signalprocessing. The authors present the work carried out towards the improvement of signalprocessing in quantitative analysis. in this paper we present the results obtain by some quantitative algorithms together with their application examples focused in the selective detection of methane and carbon.
In this paper, we present a doubly pipelined VLSI Cordic array processor for digital signalprocessing computations. The basic notion of doubly pipelined CORDIC computation will be introduced first. Then, some potenti...
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In this paper, we present a doubly pipelined VLSI Cordic array processor for digital signalprocessing computations. The basic notion of doubly pipelined CORDIC computation will be introduced first. Then, some potential applications to digital signalprocessing problems will be discussed. Specifically, we shall demonstrate how a doubly pipelined CORDIC processor array can be applied to compute discrete Fourier transform and Fast Fourier transform, to implement Lattice filters, to solve Toeplitz systems as well as matrix QR factorizations. It is shown that by adopting a secondary pipelining, about one third hardware can be saved, and sometimes the throughput of the entire CORDIC processor array may be doubled.
Presented in this paper is comparative analysis regarding the resolution of CO and MSK algorithms of radar mapping at the side looking. The analysis displays that at q ges 0 MSK algorithm has better resolution than SF...
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Presented in this paper is comparative analysis regarding the resolution of CO and MSK algorithms of radar mapping at the side looking. The analysis displays that at q ges 0 MSK algorithm has better resolution than SF, but its signalnoise ratio at the output is worse.
An overview is presented of a model for describing data and control flow associated with the execution of large-grained, decision-free algorithms in a special distributed computer environment. The ATAMM (Algorithm-To-...
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An overview is presented of a model for describing data and control flow associated with the execution of large-grained, decision-free algorithms in a special distributed computer environment. The ATAMM (Algorithm-To-Architecture Mapping Model) model provides a basis for relating an algorithm to its execution in a dataflow multicomputer environment. The ATAMM model features a marked graph Petri net description of the algorithm behavior with regard to both data and control flow. The model provides an analytical basis for calculating performance bounds on throughput characteristics which are demonstrated here.< >
In this paper we use statistical approach to synthesize algorithms for digital signalprocessing in UWB noise radar and sodar. Parametrical and non-parametrical algorithms are synthesized and analyzed. Experimental ch...
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In this paper we use statistical approach to synthesize algorithms for digital signalprocessing in UWB noise radar and sodar. Parametrical and non-parametrical algorithms are synthesized and analyzed. Experimental check is done on the basis of developed acoustic physical model which is used to build a noise sodar prototype. Developed algorithms can be used in noise radars for different applications. The use of the UWB noise signal provides a very high resolution both in speed and range
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