Results 21 to 30 of about 22,377,175 (350)
Chaff identification method based on Range‐Doppler imaging feature
IET Radar, Sonar & Navigation, 2022 Chaff is widely used in electronic countermeasures as an effective passive jamming method. This study proposes a chaff identification method that integrates the distribution of distance, Doppler frequency, and power in Range‐Doppler imaging.
Husheng Wang +8 more
doaj +1 more source
Olfactory signal processing [PDF]
Digital Signal Processing, 2016 Olfaction, the sense of smell, has received scant attention from a signal processing perspective in comparison to audition and vision. In this paper, we develop a signal processing paradigm for olfactory signals based on new scientific discoveries including the psychophysics concept of olfactory white.
Varshney, Kush R., Varshney, Lav R.
openaire +2 more sources
Intelligent Radar Jamming Recognition in Open Set Environment Based on Deep Learning Networks
Remote Sensing, 2022 Jamming recognition is an essential step in radar detection and anti-jamming in the complex electromagnetic environment. When radars detect an unknown type of jamming that does not occur in the training set, the existing radar jamming recognition ...
Yu Zhou +5 more
doaj +1 more source
An Overview of Signal Processing Techniques for Millimeter Wave MIMO Systems [PDF]
IEEE Journal on Selected Topics in Signal Processing, 2015 Communication at millimeter wave (mmWave) frequencies is defining a new era of wireless communication. The mmWave band offers higher bandwidth communication channels versus those presently used in commercial wireless systems.
R. Heath +4 more
semanticscholar +1 more source
Convolutional neural networks for radar HRRP target recognition and rejection
EURASIP Journal on Advances in Signal Processing, 2019 Robust and efficient feature extraction is critical for high-resolution range profile (HRRP)-based radar automatic target recognition (RATR). In order to explore the correlation between range cells and extract the structured discriminative features in ...
Jinwei Wan +4 more
doaj +1 more source
8th International Multitopic Conference, 2004. Proceedings of INMIC 2004., 2018 Convolutional neural networks (CNNs) have been widely used in medical imaging applications, including brain diseases such as Alzheimer’s disease (AD) classification based on neuroimaging data.
Thomas J. Cavicchi, U. Spagnolini
semanticscholar +1 more source
Signal Processing On Cell Complexes [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2021 The processing of signals supported on non-Euclidean domains has attracted large interest recently. Thus far, such non-Euclidean domains have been abstracted primarily as graphs with signals supported on the nodes, though the processing of signals on ...
T. Roddenberry +2 more
semanticscholar +1 more source
Aircraft Target Classification Based on Correlation Features from Time-domain Echoes
Leida xuebao, 2015 This paper reports the classification of helicopters, propeller-driven aircraft, and turbojet based on differences in their time-domain modulation periods using a conventional radar system.
Du Lan +4 more
doaj +1 more source
Two-Stream Deep Fusion Network Based on VAE and CNN for Synthetic Aperture Radar Target Recognition
Remote Sensing, 2021 Usually radar target recognition methods only use a single type of high-resolution radar signal, e.g., high-resolution range profile (HRRP) or synthetic aperture radar (SAR) images. In fact, in the SAR imaging procedure, we can simultaneously obtain both
Lan Du +5 more
doaj +1 more source
Graph Signal Processing: Overview, Challenges, and Applications [PDF]
Proceedings of the IEEE, 2017 Research in graph signal processing (GSP) aims to develop tools for processing data defined on irregular graph domains. In this paper, we first provide an overview of core ideas in GSP and their connection to conventional digital signal processing, along
Antonio Ortega +4 more
semanticscholar +1 more source