Novel Generalized Low-Pass Filter with Adjustable Parameters of Exponential-Type Forgetting and Its Application to ECG Signal
Ivo Petráš
Abstract
In this paper, a novel form of the Gaussian filter, the Mittag-Leffler filter is presented. This new filter uses the Mittag-Leffler function in the probability-density function. Such Mittag-Leffler distribution is used in the convolution kernel of the filter. The filter has three parameters that may adjust the curve shape due to the filter-forgetting factor. Illustrative examples present the main advantages of the proposed filter compared to classical Gaussian filtering techniques, as well as real ECG-signal denoising. Some implementation notes, along with the Matlab function, are also presented.
Topics & Concepts
Kernel adaptive filterFilter (signal processing)Low-pass filterGaussian filterConvolution (computer science)GaussianMathematicsControl theory (sociology)AlgorithmComputer scienceFilter designAdaptive filterGaussian functionRaised-cosine filterRoot-raised-cosine filterArtificial intelligenceComputer visionPhysicsArtificial neural networkControl (management)Quantum mechanicsImage (mathematics)ECG Monitoring and AnalysisImage and Signal Denoising MethodsBlind Source Separation Techniques