Search Results for author:
Found 5 papers, 1 papers with code
Solving Inverse Problems with Model Mismatch using Untrained Neural Networks within Model-based Architectures
Model-based deep learning methods such as \emph{loop unrolling} (LU) and \emph{deep equilibrium model} (DEQ) extensions offer outstanding performance in solving inverse problems (IP).
Review of Contemporary Energy Harvesting Techniques and Their Feasibility in Wireless Geophones
However, due to the random and intermittent nature of the harvested energy, it is important that geophones must be equipped to tap from several energy sources for a stable operation.
Learned Proximal Operator for Solving Seismic Deconvolution Problem
Due to the sparse nature of the reflectivity sequence, spike-promoting regularizers such as the $\ell_1$-norm are frequently used.
Short-Term Load Forecasting using Bi-directional Sequential Models and Feature Engineering for Small Datasets
Electricity load forecasting enables the grid operators to optimally implement the smart grid's most essential features such as demand response and energy efficiency.
Microseismic events enhancement and detection in sensor arrays using autocorrelation based filtering
Passive microseismic data are commonly buried in noise, which presents a significant challenge for signal detection and recovery.
