Results 201 to 210 of about 457 (225)
Terrestrial Analogs to Titan for Geophysical Research
Abstract Saturn's moon Titan exhibits remarkable parallels to the Earth in many geophysical and geological processes not found elsewhere in the solar system at the present day. These include a nitrogen atmosphere with a condensible gas—methane—replacing the Earth's water, leading to an active meteorology with rainfall and surface manifestations ...
Conor A. Nixon +21 more
wiley +1 more source
Rock Physics of the Critical Zone: Models, Inversion, and Interpretation
Abstract Rock physics models link geophysical measurements with subsurface petrophysical properties, such as porosity, mineral composition, and fluid saturation. While originally developed for hydrocarbon exploration, these models are increasingly applied in the near surface for quantitative interpretation of geophysical data.
Dario Grana +5 more
wiley +1 more source
Optimization of a Navigation System for Autonomous Charging of Intelligent Vehicles Based on the Bidirectional A* Algorithm and YOLOv11n Model. [PDF]
Liao S, Zhang L, He Y, Zhang J, Sun J.
europepmc +1 more source
Super-resolution diffractive neural network for all-optical direction of arrival estimation beyond diffraction limits. [PDF]
Gao S +7 more
europepmc +1 more source
A Comprehensive Survey on Deep Learning-Based LoRa Radio Frequency Fingerprinting Identification. [PDF]
Ahmed A, Quoitin B, Gros A, Moeyaert V.
europepmc +1 more source
Over-the-Air Radar Emitter Signal Classification Based on SDR
At present, in the field of radar emitter classification, theoretical simulation is mostly used to carry out algorithm research. However, there are few schemes to study signal classification in real electromagnetic environment using actual hardware. Therefore, this paper proposes a radar emitter classification scheme based on HackRF Software Defined ...
Yan Xia, Zhiyuan Ma, Zhi Huang
exaly +4 more sources
Radar emitter signal classification based on mutual information and fuzzy support vector machines
In this paper, a novel method based on mutual information and fuzzy support vector machines for recognizing radar emitter signals is introduced. The radar signal waveforms are the linear frequency modulation (LFM), frequency-coded signals, BPSK and QPSK. The wavelet ridges and higher-order statistics are used to extract signal features.
null Mingqiu Ren +3 more
exaly +4 more sources

