Harbin Engineering University

About: Harbin Engineering University is a education organization based out in Harbin, Heilongjiang, China. It is known for research contribution in the topics: Control theory & Computer science. The organization has 31149 authors who have published 27940 publications receiving 276787 citations. The organization is also known as: HEU.

Complex-Valued Networks for Automatic Modulation Classification

Abstract: Deep learning (DL) has been recognized as an effective solution for automatic modulation classification (AMC). However, most recent DL based AMC works are based on real-valued operations and representations. In this correspondence, we aim to demonstrate the high potential of complex-valued networks for AMC. We present the design of several key building blocks for complex-valued networks, such as complex convolution, complex batch-normalization, complex weight initialization, and complex dense strategies. We then provide a comparison study of three different neural network models and their complex-valued counterparts using the RadioML 2016.10 A dataset. Our results validate the superior performance in AMC achieved by the complex-valued networks.

Amorphous, Crystalline and Crystalline/Amorphous Selenium Nanowires and Their Different (De)Lithiation Mechanisms

Abstract: Selenium is applied as the cathode material of lithium/selenium (Li–Se) battery, which has high theoretical volumetric capacity density (3253 mA h·cm–3) and high output voltages. However, it has a low melting point (494 K) and a large sensitivity to thermal treatment, which often result in the phase transition between crystalline Se (trigonal phase) and amorphous Se during the charge/discharge cycles of Li–Se battery as reported in literatures. In order to clarify the different chemical (de)lithiation mechanisms between them in Li–Se battery, in this work large-area amorphous selenium (a-Se) nanowires (NWs) have been successfully prepared first through a facile high-energy ball-milling method. Subsequently the crystalline (c) and crystalline/amorphous (c/a) selenium NWs have also been prepared through annealing the above as-obtained amorphous products, respectively. The affirmative composition and morphology of the as-obtained Se nanostructures have been demonstrated by the XRD, SEM, TEM, HRTEM and Raman ...

An implementation of evolutionary computation for path planning of cooperative mobile robots

Abstract: This article describes how to apply a genetic algorithm in finding a globally sub-optimal path for the robot group working under certain tasks. Path planning is an important problem in robotics. With the development of cooperative robotics in recent years, the problem of path planning for a robot group is receiving more and more attention and interest. In this paper, the problem of path planning for a robot group is formalized as a multiple travelling salesman problem (MTSP) that employed either total-path-shortest or longest-path-shortest as the evaluating criterion. Longest-path-shortest MTSP has never been studied before. The formalized models of the two kinds of multiple travelling salesman problem are presented in this paper, and the main idea and specific way of applying the genetic algorithm in solving the two kinds of travelling salesman problem or their admixture are also amply discussed in this paper. At the end the convergence analysis and the simulation are discussed, as the simulation result shows, it is an effective and robust way of solving the problem of path planning for a robot group.