Search results for "Senyal"
showing 5 items of 5 documents
Climatology of the aerosol extinction-to-backscatter ratio from sun-photometric measurements
2010
The elastic lidar equation contains two unknown atmospheric parameters, namely, the particulate optical extinction and backscatter coefficients, which are related through the lidar ratio (i.e., the particulate-extinction-to-backscatter ratio). So far, independent inversion of the lidar signal has been carried out by means of Raman lidars (usually limited to nighttime measurements), high-spectral-resolution lidars, or scanning elastic lidars under the assumption of a homogeneously vertically stratified atmosphere. In this paper, we present a procedure to obtain the lidar ratio at 532 nm by a combined Sunphotometer– aerosol-model inversion, where the viability of the solution is largely reinf…
Aerosol Lidar Intercomparison in the Framework of SPALINET—The Spanish Lidar Network: Methodology and Results
2009
Abstract—A group of eight Spanish lidars was formed in order to extend the European Aerosol Research Lidar Network–Advanced Sustainable Observation System (EARLINET-ASOS)project. This study presents intercomparisons at the hardware and software levels. Results of the system intercomparisons are based on range-square-corrected signals in cases where the lidars viewed the same atmospheres. Comparisons were also made for aeros backscatter coefficients at 1064 nm (2 systems) and 532 nm (all systems), and for extinction coefficients at 532 nm (2 systems). In total, three field campaigns were carried out between 2006 and 2007. Comparisons were limited to the highest layer found before the free tr…
A Trajectory-Driven 3D Channel Model for Human Activity Recognition
2021
This paper concerns the design, analysis, and simulation of a 3D non-stationary channel model fed with inertial measurement unit (IMU) data. The work in this paper provides a framework for simulating the micro-Doppler signatures of indoor channels for human activity recognition by using radiofrequency-based sensing technologies. The major human body segments, such as wrists, ankles, torso, and head, are modelled as a cluster of moving point scatterers. We provide expressions for the time variant (TV) speed and TV angles of motion based on 3D trajectories of the moving person. Moreover, we present mathematical expressions for the TV Doppler shifts and TV path gains associated with each movin…
WiWeHAR: Multimodal Human Activity Recognition Using Wi-Fi and Wearable Sensing Modalities
2020
Robust and accurate human activity recognition (HAR) systems are essential to many human-centric services within active assisted living and healthcare facilities. Traditional HAR systems mostly leverage a single sensing modality (e.g., either wearable, vision, or radio frequency sensing) combined with machine learning techniques to recognize human activities. Such unimodal HAR systems do not cope well with real-time changes in the environment. To overcome this limitation, new HAR systems that incorporate multiple sensing modalities are needed. Multiple diverse sensors can provide more accurate and complete information resulting in better recognition of the performed activities. This article…
Signal-to-noise ratio in reproducing kernel Hilbert spaces
2018
This paper introduces the kernel signal-to-noise ratio (kSNR) for different machine learning and signal processing applications}. The kSNR seeks to maximize the signal variance while minimizing the estimated noise variance explicitly in a reproducing kernel Hilbert space (rkHs). The kSNR gives rise to considering complex signal-to-noise relations beyond additive noise models, and can be seen as a useful signal-to-noise regularizer for feature extraction and dimensionality reduction. We show that the kSNR generalizes kernel PCA (and other spectral dimensionality reduction methods), least squares SVM, and kernel ridge regression to deal with cases where signal and noise cannot be assumed inde…