ADMM-Net: A Deep Learning Approach for Parameter Estimation of Chirp Signals Under Sub-Nyquist Sampling.
Hanning SuQinglong BaoZengping ChenPublished in: IEEE Access (2020)
Keyphrases
- parameter estimation
- deep learning
- fractional fourier transform
- sampling rate
- markov chain monte carlo
- instantaneous frequency
- maximum likelihood
- unsupervised learning
- least squares
- model selection
- em algorithm
- expectation maximization
- markov random field
- random fields
- parameter estimation algorithm
- machine learning
- weakly supervised
- signal processing
- approximate inference
- higher order
- mental models
- multiscale
- image processing
- pairwise
- reinforcement learning