Results 31 to 40 of about 784,273 (337)

The design and implementation of folded adaptive lattice filter structures in FPGA for ECG signals

open access: yesAutomatika, 2023
An adaptive filter is the utmost essential filter castoff in statistical signal dealing. The fine-tuning of the filter factor in relation to the response signal is the adaptive filter's key feature due to fewer calculations, Least Mean Square (LMS ...
Kalamani C.   +3 more
doaj   +1 more source

Unified Linearization-based Nonlinear Filtering [PDF]

open access: yesarXiv, 2023
This letter shows that the following three classes of recursive state estimation filters: standard filters, such as the extended Kalman filter; iterated filters, such as the iterated unscented Kalman filter; and dynamically iterated filters, such as the dynamically iterated posterior linearization filters; can be unified in terms of a general algorithm.
arxiv  

Review of Fundamental Active Current Extraction Techniques for SAPF

open access: yesSensors, 2022
The field of advanced digital signal processing methods is one of the fastest developing scientific and technical disciplines, and is important in the field of Shunt Active Power Filter control methods.
Jan Baros   +6 more
doaj   +1 more source

Application of Derivative Transform Spectroscopy in Gas Detection [PDF]

open access: yesE3S Web of Conferences, 2021
Digital filtering technique is of great significance in real-time signal processing and analysis, but the stability, efficiency and flexibility of filter algorithm are important indicators to reflect its application value.
Chen Tingting   +3 more
doaj   +1 more source

On semi shift invariant graph filters [PDF]

open access: yesarXiv, 2022
In graph signal processing, one of the most important subjects is the study of filters, i.e., linear transformations that capture relations between graph signals. One of the most important families of filters is the space of shift invariant filters, defined as transformations commute with a preferred graph shift operator. Shift invariant filters have a
arxiv  

Graph Filters for Signal Processing and Machine Learning on Graphs [PDF]

open access: yesarXiv, 2022
Filters are fundamental in extracting information from data. For time series and image data that reside on Euclidean domains, filters are the crux of many signal processing and machine learning techniques, including convolutional neural networks. Increasingly, modern data also reside on networks and other irregular domains whose structure is better ...
arxiv  

Signal acquisition and processing method for capacitive electromagnetic flowmeter

open access: yesJournal of Electronic Science and Technology, 2021
A kind of signal acquisition circuit and the related signal processing method of the capacitance electromagnetic flowmeter were introduced. The circuit can eliminate the influence of distributed capacitance on the input impedance of the operational ...
Hong-Yu Yang, Yan Chen, Hui Zhao
doaj  

Programming of digital linear phase filter in ARMv8 architecture

open access: yesТруды Института системного программирования РАН, 2019
We consider the problem of using processors with an ARMv8 architecture to speed up the operation of multimedia algorithms and digital processing when solving problems of signal recovery in the filtering process.
A. M. Vodovozov, D. S. Poletaev
doaj   +1 more source

A Coordinate System Choice when Information Signal Processing by Kalman Filter

open access: yesСовременные информационные технологии и IT-образование, 2021
The article describes information signal smoothing problems in the technical systems with movable platform. In such technical systems different coordinate system are used and there is a signal conditioning from one coordinate system into one another when
Valeriy Ponyatsky
doaj   +1 more source

Nonlinear filtering for LIDAR signal processing

open access: yesMathematical Problems in Engineering, 1996
LIDAR (Laser Integrated Radar) is an engineering problem of great practical importance in environmental monitoring sciences. Signal processing for LIDAR applications involves highly nonlinear models and consequently nonlinear filtering. Optimal nonlinear filters, however, are practically unrealizable.
Lainiotis, D. G.   +2 more
openaire   +3 more sources

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