Soft Consistency Reconstruction: A Robust 1-bit Compressive Sensing Algorithm

A class of recovering algorithms for 1-bit compressive sensing (CS) named Soft Consistency Reconstructions (SCRs) are proposed. Recognizing that CS recovery is essentially an optimization problem, we endeavor to improve the characteristics of the objective function under noisy environments. With a family of re-designed consistency criteria, SCRs achieve remarkable counter-noise performance gain over the existing counterparts, thus acquiring the desired robustness in many real-world applications. The benefits of soft decisions are exemplified through structural analysis of the objective function, with intuition described for better understanding. As expected, through comparisons with existing methods in simulations, SCRs demonstrate preferable robustness against noise in low signal-to-noise ratio (SNR) regime, while maintaining comparable performance in high SNR regime

Research on wind pressure and wind-induced vibration characteristics of expo axis cable-membrane structure by field measurement

In order to deeply investigate the wind pressure characteristics and the windinduced vibration characteristics of cable-membrane structure, a monitoring study on the Expo Axis cable-membrane structure was carried out. The wind speed, wind pressure and wind-induced response were measured simultaneously. The wind pressure characteristics, the structure’s dynamic characteristics and the damping ratio were analyzed based on the monitoring data. The probability density distribution of wind pressure has some non-Gauss property. With the change of wind direction wind pressure coefficient by field measurement and wind tunnel test has the same trend. The acceleration RMS and power spectral density vary with the wind direction. The acceleration RMS increases with the increase of mean wind speed. Damping ratio decreases with the increase of natural frequency