스펙트럼 검출 및 변조 분류
다음 예제에서는 스펙트럼 검출 및 변조 분류에 사용할 수 있는 AI 기술을 보여줍니다.
추천 예제
Apply Transfer Learning on PyTorch Model to Identify 5G and LTE Signals
Coexecution with Python to identify 5G NR and LTE signals by using the transfer learning technique on a pre-trained PyTorch™ semantic segmentation network for spectrum sensing.
Spectrum Sensing with Deep Learning to Identify 5G, LTE, and WLAN Signals
Train a semantic segmentation network using deep learning for spectrum monitoring.
Capture and Label NR and LTE Signals for AI Training
Scan, capture, and label bandwidths with 5G NR and LTE signals.
Identify LTE and NR Signals from Captured Data Using SDR and Deep Learning
Use a spectrum sensing neural network to identify LTE and NR signals from wireless data you capture over the air.
Modulation Classification by Using FPGA
Deploy a pretrained convolutional neural network (CNN) for modulation classification to the Xilinx® Zynq® UltraScale+™ MPSoC ZCU102 Evaluation Kit.
딥러닝을 사용한 변조 분류
변조 분류에 컨벌루션 신경망(CNN)을 사용합니다.
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).
