Some fundamental properties on the sampling free nabla Laplace transform

Discrete fractional order systems have attracted more and more attention in recent years. Nabla Laplace transform is an important tool to deal with the problem of nabla discrete fractional order systems, but there is still much room for its development. In this paper, 14 lemmas are listed to conclude the existing properties and 14 theorems are developed to describe the innovative features. On one hand, these properties make the N-transform more effective and efficient. On the other hand, they enrich the discrete fractional order system theor

Description and Realization for a Class of Irrational Transfer Functions

This paper proposes an exact description scheme which is an extension to the well-established frequency distributed model method for a class of irrational transfer functions. The method relaxes the constraints on the zero initial instant by introducing the generalized Laplace transform, which provides a wide range of applicability. With the discretization of continuous frequency band, the infinite dimensional equivalent model is approximated by a finite dimensional one. Finally, a fair comparison to the well-known Charef method is presented, demonstrating its added value with respect to the state of art.Comment: 9 pages, 9 figure

On Big Data and Hydroinformatics:12th International Conference on Hydroinformatics (HIC 2016) - Smart Water for the Future

AbstractBig data is an increasingly hot concept in the past five years in the area of computer science, e-commence, and bioinformatics, because more and more data has been collected by the internet, remote sensing network, wearable devices and the Internet of Things. The big data technology provides techniques and analytical tools to handle large datasets, so that creative ideas and new values can be extracted from them. However, the hydroinformatics research community are not so familiar with big data. This paper provides readers who are embracing the data-rich era with a timely review on big data and its relevant technology, and then points out the relevance with hydroinformatics in three aspects

Big data and hydroinformatics

Big data is popular in the areas of computer science, commerce and bioinformatics, but is in an early stage in hydroinformatics. Big data is originated from the extremely large datasets that cannot be processed in tolerable elapsed time with the traditional data processing methods. Using the analogy from the object-oriented programming, big data should be considered as objects encompassing the data, its characteristics and the processing methods. Hydroinformatics can benefit from the big data technology with newly emerged data, techniques and analytical tools to handle large datasets, from which creative ideas and new values could be mined. This paper provides a timely review on big data with its relevance to hydroinformatics. A further exploration on precipitation big data is discussed because estimation of precipitation is an important part of hydrology for managing floods and droughts, and understanding the global water cycle. It is promising that fusion of precipitation data from remote sensing, weather radar, rain gauge and numerical weather modelling could be achieved by parallel computing and distributed data storage, which will trigger a leap in precipitation estimation as the available data from multiple sources could be fused to generate a better product than those from single sources.</jats:p

Partially Nondestructive Continuous Detection of Individual Traveling Optical Photons

We report the continuous and partially nondestructive measurement of optical photons. For a weak light pulse traveling through a slow-light optical medium (signal), the associated atomic-excitation component is detected by another light beam (probe) with the aid of an optical cavity. We observe strong correlations of $g^{(2)}_{sp}=4.4(5)$ between the transmitted signal and probe photons. The observed (intrinsic) conditional nondestructive quantum efficiency ranges between 13% and 1% (65% and 5%) for a signal transmission range of 2% to 35%, at a typical time resolution of 2.5 $\mu$s. The maximal observed (intrinsic) device nondestructive quantum efficiency, defined as the product of the conditional nondestructive quantum efficiency and the signal transmission, is 0.5% (2.4%). The normalized cross-correlation function violates the Cauchy-Schwarz inequality, confirming the non-classical character of the correlations

Analytical calculation of the inverse nabla Laplace transform

The inversion of nabla Laplace transform, corresponding to a causal sequence, is considered. Two classical methods, i.e., residual calculation method and partial fraction method are developed to perform the inverse nabla Laplace transform. For the first method, two alternative formulae are proposed when adopting the poles inside or outside of the contour, respectively. For the second method, a table on the transform pairs of those popular functions is carefully established. Besides illustrating the effectiveness of the developed methods with two illustrative examples, the applicability are further discussed in the fractional order case

Improving Autonomous Vehicle Mapping and Navigation in Work Zones Using Crowdsourcing Vehicle Trajectories

Prevalent solutions for Connected and Autonomous vehicle (CAV) mapping include high definition map (HD map) or real-time Simultaneous Localization and Mapping (SLAM). Both methods only rely on vehicle itself (onboard sensors or embedded maps) and can not adapt well to temporarily changed drivable areas such as work zones. Navigating CAVs in such areas heavily relies on how the vehicle defines drivable areas based on perception information. Difficulties in improving perception accuracy and ensuring the correct interpretation of perception results are challenging to the vehicle in these situations. This paper presents a prototype that introduces crowdsourcing trajectories information into the mapping process to enhance CAV's understanding on the drivable area and traffic rules. A Gaussian Mixture Model (GMM) is applied to construct the temporarily changed drivable area and occupancy grid map (OGM) based on crowdsourcing trajectories. The proposed method is compared with SLAM without any human driving information. Our method has adapted well with the downstream path planning and vehicle control module, and the CAV did not violate driving rule, which a pure SLAM method did not achieve.Comment: Presented at TRBAM. Journal version in progres