Radar e Wireless
R2026bClassifica i bersagli radar e le forme d'onda utilizzando modelli di Deep Learning. Identifica pedoni e ciclisti e utilizzare reti neurali a grafo per allocare le risorse wireless.
Informazioni complementari
Esempi in primo piano
CBRS Band Radar Detection in 5G Signals and Noise Using YOLOX
Detect rectangular and linear-FM radar pulse waveforms embedded in a 5G+noise environment using a combination of time-frequency maps and a deep learning object detector.
- Da R2026b
- Apri live script
Automated Labeling of Time-Frequency Regions for AI-Based Spectrum Sensing Applications
Use rule-based methods or unsupervised learning techniques to help automate time-frequency data labeling.
- Da R2025a
- Apri live script
Export Labeled Data from Signal Labeler for AI-Based Spectrum Sensing Applications
Use deep learning networks and the Signal Labeler app to identify frames from the Bluetooth® and Wi-Fi® wireless standards.
- Da R2025a
- Apri live script
Wireless Resource Allocation Using Graph Neural Network
Use graph neural networks for power allocation in wireless networks.
- Da R2024b
- Apri live script
CBRS Band Radar Parameter Estimation Using YOLOX
Detect radar pulses in noise and estimate the pulse parameters using a combination of time-frequency maps and a deep-learning object detector.
- Da R2025a
- Apri live script
Direction-of-Arrival Estimation Using Deep Learning
Estimate direction of arrival using deep learning by predicting angular directions directly from the sample covariance matrix.
- Da R2025a
- Apri live script
Pedestrian and Bicyclist Classification Using Deep Learning
Classify pedestrians and bicyclists based on their micro-Doppler characteristics using deep learning and time-frequency analysis.
(Radar Toolbox)
Radar and Communications Waveform Classification Using Deep Learning
Classify radar and communications waveforms using the Wigner-Ville distribution (WVD) and a deep convolutional neural network (CNN).
(Phased Array System Toolbox)
Radar Target Classification Using Machine Learning and Deep Learning
Classify radar returns using machine and deep learning approaches.
(Radar Toolbox)
LPI Radar Waveform Classification Using Time-Frequency CNN
Train a time-frequency convolutional neural network (CNN) to classify received radar waveforms based on modulation scheme.
(Radar Toolbox)
- Da R2024a
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