Search results for "Finite impulse response"

showing 10 items of 23 documents

Improving accuracy of FIR filters for computing convolution transforms for smooth non-bandlimited signals

2019

We propose to improve the accuracy of FIR filters for computing convolution transforms for smooth non-bandlimited (NBL) signals by designing filters by the identification method with using a pair of bandlimited portions of the chosen NBL input and output signals related with each other by the given transform. A design example of type IV linear phase differentiator is presented, where filter coefficients are calculated from the bandlimited portions of the Cauchy pulse and its derivative. The performance of the designed differentiator is evaluated by comparing the accuracy of computed derivatives for several smooth NBL test signals, such as the Cauchy pulse, the Hilbert transform of Cauchy pu…

Bandlimiting020303 mechanical engineering & transports0203 mechanical engineeringFinite impulse responseComputer sciencelcsh:TA1-2040021105 building & construction0211 other engineering and technologies02 engineering and technologylcsh:Engineering (General). Civil engineering (General)AlgorithmConvolutionMATEC Web of Conferences
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Introduction: Digital Filters and Filter Banks

2015

A basic operation of spectr is filterin. In this introductory chapter, processing of one- and two-dimensional signals by digital filters and filter banks is outlined. A polyphase implementation of multirate filtering is described. The application of filtering with IIR filters, whose transfer functions are rational, is described. Bases and frames in the signals’ space that are generated by perfect reconstruction filter banks are discussed. The Butterworth filters, which are used in further constructions, are introduced.

Computer scienceElectronic engineeringPolyphase systemButterworth filterFilter (signal processing)Capacitor-input filterFilter bankTransfer functionInfinite impulse responseDigital filter
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Nonlinear System Response for Impulsive Parametric Input

1997

In engineering applications when the intensity of external forces depends on the response of the system, the input is called parametric. In this paper dynamical systems subjected to a parametric deterministic impulse are dealt with. Particular attention has been devoted to the evaluation of the discontinuity of the response when the parametric impulse occurs. The usual forward difference and trapezoidal integration schemes have been shown to provide only approximated solutions of the jump of the response; hence, the exact solution has been pursued and presented under the form of a numerical series. The impulse is represented throughout the paper by means of a classical Dirac’s delta functio…

Dynamical systems theoryFinite impulse responseMechanical EngineeringFinite differenceDirac delta functionImpulse (physics)Condensed Matter Physicssymbols.namesakeMechanics of MaterialsControl theorysymbolsApplied mathematicsInfinite impulse responseImpulse responseMathematicsParametric statisticsJournal of Applied Mechanics
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Narrowband digital filtering with random frequency hopping spread spectrum

2014

International audience; In digital signal filtering, channels with narrow bandwidth need high order digital filter to be selected without introducing modulation errors. If a carrier randomly switches from a channel to another as in military applications, or some civilian communication standards, it is necessary to detect and estimate these jumps before transposing and analyzing signals in the baseband. This paper presents a real time solution to filter narrow band signals with random frequency hopping spread spectrum. The proposed method is based on three steps. Firstly, the detection of Signal Frequency Hopping (SFH) using the Fast Fourier Transform (FFT), an algorithm to estimate the Domi…

Engineering[ INFO ] Computer Science [cs]Finite impulse responsebusiness.industryLow-pass filter020206 networking & telecommunicationsGSM modulation02 engineering and technologyFilter (signal processing)Frequency hoppingSpread spectrumFPG[SPI]Engineering Sciences [physics][ SPI ] Engineering Sciences [physics]0202 electrical engineering electronic engineering information engineeringBasebandElectronic engineeringFrequency-hopping spread spectrumDigital signal[INFO]Computer Science [cs]High selectivitybusinessnarrow band filteringDigital filter
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A Memetic Differential Evolution in Filter Design for Defect Detection in Paper Production

2007

This article proposes a Memetic Differential Evolution (MDE) for designing digital filters which aim at detecting defects of the paper produced during an industrial process. The MDE is an adaptive evolutionary algorithm which combines the powerful explorative features of Differential Evolution (DE) with the exploitative features of two local searchers. The local searchers are adaptively activated by means of a novel control parameter which measures fitness diversity within the population. Numerical results show that the DE framework is efficient for the class of problems under study and employment of exploitative local searchers is helpful in supporting the DE explorative mechanism in avoid…

Engineeringeducation.field_of_studyFinite impulse responsebusiness.industryProcess (engineering)PopulationEvolutionary algorithmMachine learningcomputer.software_genreFilter designDifferential evolutionMemetic algorithmArtificial intelligencebusinesseducationcomputerDigital filter
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Foetal ECG recovery using dynamic neural networks

2002

Non-invasive electrocardiography has proven to be a very interesting method for obtaining information about the foetus state and thus to assure its well-being during pregnancy. One of the main applications in this field is foetal electrocardiogram (ECG) recovery by means of automatic methods. Evident problems found in the literature are the limited number of available registers, the lack of performance indicators, and the limited use of non-linear adaptive methods. In order to circumvent these problems, we first introduce the generation of synthetic registers and discuss the influence of different kinds of noise to the modelling. Second, a method which is based on numerical (correlation coe…

Finite impulse responseComputer scienceMedicine (miscellaneous)Machine learningcomputer.software_genreSensitivity and SpecificityLeast mean squares filterElectrocardiographyFetal HeartPredictive Value of TestsPregnancyArtificial IntelligenceRobustness (computer science)HumansActive noise controlArtificial neural networkbusiness.industryModels CardiovascularPattern recognitionAdaptive filterIdentification (information)NoiseFemaleNeural Networks ComputerArtificial intelligencebusinesscomputerArtificial Intelligence in Medicine
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Introduction: Periodic Filters and Filter Banks

2014

In this chapter filtering of periodic signals is outlined. Periodic filters and periodic filter banks are defined. Perfect reconstruction filter banks are characterized via their polyphase matrices.

Finite impulse responseComputer sciencePeriodic sequencePolyphase systemFilter (signal processing)Capacitor-input filterTopologyX-ray filterInfinite impulse responseImpulse responseComputer Science::Other
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Explicit Recursive and Adaptive Filtering in Reproducing Kernel Hilbert Spaces

2014

This brief presents a methodology to develop recursive filters in reproducing kernel Hilbert spaces. Unlike previous approaches that exploit the kernel trick on filtered and then mapped samples, we explicitly define the model recursivity in the Hilbert space. For that, we exploit some properties of functional analysis and recursive computation of dot products without the need of preimaging or a training dataset. We illustrate the feasibility of the methodology in the particular case of the $\gamma$ -filter, which is an infinite impulse response filter with controlled stability and memory depth. Different algorithmic formulations emerge from the signal model. Experiments in chaotic and elect…

Mathematical optimizationComputer Networks and Communications02 engineering and technologyautoregressive and moving-averagekernel methodssymbols.namesakeArtificial Intelligence0202 electrical engineering electronic engineering information engineeringKernel adaptive filterInfinite impulse responseMathematicsfilterrecursiveHilbert space020206 networking & telecommunicationsFilter (signal processing)AdaptiveComputer Science ApplicationsAdaptive filterKernel methodKernel (statistics)symbols020201 artificial intelligence & image processingAlgorithmSoftwareReproducing kernel Hilbert spaceIEEE Transactions on Neural Networks and Learning Systems
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Explicit recursivity into reproducing kernel Hilbert spaces

2011

This paper presents a methodology to develop recursive filters in reproducing kernel Hilbert spaces (RKHS). Unlike previous approaches that exploit the kernel trick on filtered and then mapped samples, we explicitly define model recursivity in the Hilbert space. The method exploits some properties of functional analysis and recursive computation of dot products without the need of pre-imaging. We illustrate the feasibility of the methodology in the particular case of the gamma-filter, an infinite impulse response (IIR) filter with controlled stability and memory depth. Different algorithmic formulations emerge from the signal model. Experiments in chaotic and electroencephalographic time se…

Mathematical optimizationgamma filterHilbert spaceDot productFilter (signal processing)pre-imagefunctional analysissymbols.namesakekernel methodsKernel methodKernel (statistics)symbolsRecursive filterInfinite impulse responseAlgorithmMathematicsReproducing kernel Hilbert spaceRecursive filter
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Therapeutic Drug Monitoring of Kidney Transplant Recipients Using Profiled Support Vector Machines

2007

This paper proposes a twofold approach for therapeutic drug monitoring (TDM) of kidney recipients using support vector machines (SVMs), for both predicting and detecting Cyclosporine A (CyA) blood concentrations. The final goal is to build useful, robust, and ultimately understandable models for individualizing the dosage of CyA. We compare SVMs with several neural network models, such as the multilayer perceptron (MLP), the Elman recurrent network, finite/infinite impulse response networks, and neural network ARMAX approaches. In addition, we present a profile-dependent SVM (PD-SVM), which incorporates a priori knowledge in both tasks. Models are compared numerically, statistically, and in…

Mean squared errorComputer sciencecomputer.software_genreBlood concentrationmedicineElectrical and Electronic EngineeringInfinite impulse responseKidney transplantationArtificial neural networkmedicine.diagnostic_testbusiness.industryPattern recognitionmedicine.diseaseComputer Science ApplicationsHuman-Computer InteractionSupport vector machineNoiseAutoregressive modelControl and Systems EngineeringTherapeutic drug monitoringMultilayer perceptronData miningArtificial intelligencebusinesscomputerSoftwareInformation SystemsIEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)
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