Huawei

About: Huawei is a company organization based out in Shenzhen, China. It is known for research contribution in the topics: Terminal (electronics) & Node (networking). The organization has 41417 authors who have published 44698 publications receiving 343496 citations. The organization is also known as: Huawei Technologies & Huawei Technologies Co., Ltd..

Generative Feature Replay For Class-Incremental Learning

Abstract: Humans are capable of learning new tasks without forgetting previous ones, while neural networks fail due to catastrophic forgetting between new and previously-learned tasks. We consider a class-incremental setting which means that the task-ID is unknown at inference time. The imbalance between old and new classes typically results in a bias of the network towards the newest ones. This imbalance problem can either be addressed by storing exemplars from previous tasks, or by using image replay methods. However, the latter can only be applied to toy datasets since image generation for complex datasets is a hard problem.We propose a solution to the imbalance problem based on generative feature replay which does not require any exemplars. To do this, we split the network into two parts: a feature extractor and a classifier. To prevent forgetting, we combine generative feature replay in the classifier with feature distillation in the feature extractor. Through feature generation, our method reduces the complexity of generative replay and prevents the imbalance problem. Our approach is computationally efficient and scalable to large datasets. Experiments confirm that our approach achieves state-of-the-art results on CIFAR-100 and ImageNet, while requiring only a fraction of the storage needed for exemplar-based continual learning. Code available at https://github.com/xialeiliu/GFR-IL.

Undersampled-Based Modulation Schemes for Optical Camera Communications

Abstract: Widespread use of white light-emitting diodes and ubiquitous smart devices offer the opportunity to establish VLC, which has become a hot research topic based on the growing number of publications over the last decade Camera-based VLC, namely OCC, provides many unique features when compared to a single-photodiode-based system, such as the ability to separate incident light in the spatial and color domains OCC technology represents a promising approach to utilize the benefits of VLC in beyond-5G scenarios and is one of the key technologies of the Internet of Things Establishing a long communication channel in OCC, as well as non-flickering illumination by using low-frame-rate camera detectors, requires special modulation schemes This article provides an overview of the principles of three categories of modulation schemes for OCC systems using a low-frame-rate camera detector In addition, a series of undersampled modulation schemes are proposed and discussed to achieve flicker-free OCC with higher spectral efficiency In addition, framing structures are designed to solve problems occurring in OCC systems using particular modulation schemes To evaluate the performance of these modulation schemes, measured bit error rate values are shown Finally, challenges in the implementation of OCC systems are also outlined

Millimeter Wave MIMO Channel Tracking Systems

Abstract: We consider channel/subspace tracking systems for temporally correlated millimeter wave (e.g., E-band) multiple-input multiple-output (MIMO) channels. Our focus is given to the tracking algorithm in the non-line-of-sight (NLoS) environment, where the transmitter and the receiver are equipped with hybrid analog/digital precoder and combiner, respectively. In the absence of straightforward time-correlated channel model in the millimeter wave MIMO literature, we present a temporal MIMO channel evolution model for NLoS millimeter wave scenarios. Considering that conventional MIMO channel tracking algorithms in microwave bands are not directly applicable, we propose a new channel tracking technique based on sequentially updating the precoder and combiner. Numerical results demonstrate the superior channel tracking ability of the proposed technique over independent sounding approach in the presented channel model and the spatial channel model (SCM) adopted in 3GPP specification.

Epileptic Signal Classification With Deep EEG Features by Stacked CNNs

Abstract: The scalp electroencephalogram (EEG)-based epileptic seizure/nonseizure detection has been comprehensively studied, and fruitful achievements have been reported in the past. Yet, few investigations have been paid to the preictal stage detection, which is practically more crucial to epileptics in taking precautions before seizure onset. In this article, a novel epileptic preictal state classification and seizure detection algorithm based on deep features learned by stacked convolutional neural networks (SCNNs) is developed. The mean amplitude of sub-band spectrum map (MAS) obtained from the average sub-band spectra of multichannel EEGs is adopted for representation. The probability feature vectors by stacked convolutional neural networks (CNNs) are extracted in the softmax layer of CNNs, where an adaptive and discriminative feature weighting fusion (AWF) is developed for performance enhancement. Following the deep extraction layer, the effective kernel extreme learning machine (KELM) is adopted for feature learning and epileptic classification. Experiments on the benchmark CHB-MIT database and a real recorded epileptic database are conducted for performance demonstration. Comparisons to many state-of-the-art epileptic classification methods are provided to show the superiority of the proposed SCNN+AWF algorithm.

Design of a Wideband Antenna With Stable Omnidirectional Radiation Pattern Using the Theory of Characteristic Modes

Abstract: In this communication, the design procedure of a wideband antenna with omnidirectional radiation pattern is demonstrated based on the theory of characteristic modes. Consisting of a dipole and a loop antenna, the antenna has a very simple structure. A wide impedance bandwidth is obtained because of the simultaneous excitation of the antenna’s first two modes. Meanwhile, due to the fact that these two modes share a similar omnidirectional radiation pattern, a stable radiation pattern is also achieved across the operating frequency band. In order to identify the antenna’s different modes, a characteristic mode analysis of the antenna is carried out first. Then, a feed configuration is specifically designed to excite the desired modes. To validate the antenna design, a prototype was fabricated and tested. Measured results agree well with the simulated ones. Measurement shows that a wide impedance bandwidth of 44.2% with $\vert {\text{S}_{11}}\vert dB (1.85–2.9 GHz) and stable radiation patterns at both E-plane and H-plane were achieved over the operating frequency band.