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レーダー処理
Deep Learning Toolbox™ を Radar Toolbox と共に使用して、レーダー システムに深層学習を適用します。信号処理アプリケーションについては、信号処理を参照してください。
注目の例
Improving Weather Radar Moment Estimation with Convolutional Neural Networks
Train and evaluate convolutional neural networks (CNN) to improve weather radar moment estimation.
LPI Radar Waveform Classification Using Time-Frequency CNN
Train a time-frequency convolutional neural network (CNN) to classify received radar waveforms based on their modulation scheme.
Generate Novel Radar Waveforms Using GAN
Generate new radar waveforms using a Wasserstein generative adversarial network with a gradient penalty (WGAN-GP).
レーダー信号と深層学習を使用した手のジェスチャの分類
MISO 畳み込みニューラル ネットワークを使用して、超広帯域インパルス レーダー信号データを分類する。
Human Health Monitoring Using Continuous Wave Radar and Deep Learning
Reconstruct electrocardiogram signals using a bidirectional long short-term memory network and wavelet multiresolution analysis.
Maritime Clutter Suppression with Neural Networks
Train and evaluate a convolutional neural network to remove clutter returns from maritime radar PPI images using the Deep Learning Toolbox™.
Pedestrian and Bicyclist Classification Using Deep Learning
Classify pedestrians and bicyclists based on their micro-Doppler characteristics using deep learning and time-frequency analysis.
Label Radar Signals with Signal Labeler
Label the time and frequency features of pulse radar signals with added noise.
Radar Target Classification Using Machine Learning and Deep Learning
Classify radar returns using machine and deep learning approaches.
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).
SAR Target Classification Using Deep Learning
Create and train a simple convolution neural network to classify SAR targets using deep learning.
