信号处理

Classify electroencephalographic (EEG) time series from persons with and without epilepsy.

Construct wavelet-based feature embeddings to classify EEG signals from persons with and without epilepsy.

Learn how to develop an alert system for predictive maintenance using wavelet scattering and deep learning.

Reconstruct electrocardiogram signals using a bidirectional long short-term memory network and wavelet multiresolution analysis.

使用深度学习和连续小波变换对心跳心电图数据进行分类。

Use wavelet-extracted features and an autoencoder to detect arc signals in a DC system.

使用时频分析和深度学习分割人体心电图信号。

Use a conditional generative adversarial network to produce synthetic data for model training.

Use a convolutional deep network to learn a pre-emphasis filter for speech recognition.

Use an adversarial learning denoiser model to denoise signals.

Use a learning-based tool to detect abnormal points or segments in time-series data.