4 papers
Neural Network Approximation of Refinable Functions
Ingrid Daubechies, Ronald DeVore, Nadav Dym +6
In the desire to quantify the success of neural networks in deep learning and other applications, there is a great interest in understanding which functions are efficiently approxi…
Three Dimensional Sums of Character Gabor Systems
Kung-Ching Lin
In deterministic compressive sensing, one constructs sampling matrices that recover sparse signals from highly incomplete measurements. However, the so-called square-root bottlenec…
Adapted Decimation on Finite Frames for Arbitrary Orders of Sigma-Delta Quantization
Kung-Ching Lin
In Analog-to-digital (A/D) conversion, signal decimation has been proven to greatly improve the efficiency of data storage while maintaining high accuracy. When one couples signal…
Analysis of Decimation on Finite Frames with Sigma-Delta Quantization
Kung-Ching Lin
In Analog-to-digital (A/D) conversion, signal decimation has been proven to greatly improve the efficiency of data storage while maintaining high accuracy. When one couples signal…