Keyphrases
Machine Learning Approach
100%
Received Signal
100%
Sparse Recovery
100%
Sparsity Recovery
100%
Compressive Spectrum Sensing
100%
Decay Rate
66%
Computational Complexity
66%
Compressed Sensing
66%
Spectrum Sensing
66%
Sub-Nyquist Sampling
66%
Sparse Coding
66%
Convergence Rate
33%
Detection Probability
33%
Narrowband
33%
Excellent Performance
33%
Classification Process
33%
Synthetic Data
33%
Recovery Process
33%
Sparsity
33%
Numerical Experiments
33%
False Alarm Rate
33%
Machine Learning Classification
33%
Gradient Vector
33%
Learned Dictionary
33%
Analog-to-digital Conversion
33%
Rate Measures
33%
Real-time Operation
33%
Spectrum Occupancy
33%
Residual Vector
33%
Real-world Measurements
33%
Location of Interest
33%
Energy Decay
33%
Gradient Operator
33%
Convergence Patterns
33%
Sample Complexity
33%
Challenging Issues
33%
Engineering
Computational Complexity
100%
Nyquist Frequency
100%
Sparse Coding
100%
Sparsity
100%
Learning Approach
100%
Compressive Sensing
100%
Learning System
100%
Probability of Detection
50%
Real Life
50%
Numerical Experiment
50%
Recovery Process
50%
Classification Process
50%
Convergence Rate
50%
False Alarm Rate
50%
Analog to Digital Conversion
50%
Spectrum Occupancy
50%
Rate Measure
50%
Gradient Vector
50%
Computer Science
Computational Complexity
100%
Compressive Sensing
100%
Sparsity
100%
Machine Learning Approach
100%
Nyquist Frequency
100%
Classification Process
50%
Synthetic Data
50%
Convergence Rate
50%
Digital Conversion
50%
Spectrum Occupancy
50%
Residual Vector
50%
False Alarm Rate
50%
Gradient Vector
50%
Compressed Version
50%
Gradient Operator
50%
Recovery Process
50%
Machine Learning
50%
Learning System
50%