6 papers
Statistical learning for train delays and influence of winter climate and atmospheric icing
Jianfeng Wang, Roberto Mantas Nakhai, Jun Yu
This study investigated the climate effect under consecutive winters on the arrival delay of high-speed passenger trains in northern Sweden. Novel statistical learning approaches,…
Train performance analysis using heterogeneous statistical models
Jianfeng Wang, Jun Yu
This study investigated the effect of harsh winter climate on the performance of high speed passenger trains in northern Sweden. Novel approaches based on heterogeneous statistical…
Effects of winter climate on high speed passenger trains in Botnia-Atlantica region
Jianfeng Wang, Markus Granlöf, Jun Yu
Harsh winter climate can cause various problems for both public and private sectors in Sweden, especially in the northern part for railway industry. To have a better understanding…
Statistical inference for block sparsity of complex signals
Jianfeng Wang, Zhiyong Zhou, Jun Yu
Block sparsity is an important parameter in many algorithms to successfully recover block sparse signals under the framework of compressive sensing. However, it is often unknown an…
Enhanced block sparse signal recovery based on -ratio block constrained minimal singular values
Jianfeng Wang, Zhiyong Zhou, Jun Yu
In this paper we introduce the -ratio block constrained minimal singular values (BCMSV) as a new measure of measurement matrix in compressive sensing of block sparse/compressive…
Sparsity estimation in compressive sensing with application to MR images
Jianfeng Wang, Zhiyong Zhou, Anders Garpebring +1
The theory of compressive sensing (CS) asserts that an unknown signal can be accurately recovered from measurements with provided that $\…