民机地形感知警告系统前视功能分析及仿真

综述了民机地形感知警告系统(TAWS)及其前视功能的产生背景、发展过程,介绍了TAWS前视功能的主要原理.对前视功能的报警阈值时间设置方法进行了研究,给出了报警阈值时间设置的分析算法模型,并利用Matlab 工具进行了仿真,得到了相应的仿真结果.最后,对进一步提高TAWS前视功能仿真精确度,以及TAWS产品性能优化方法...     

风电场随机时间序列法功率预测的探究

我国能源资源总量相对较少,人均占有率低;能源消费增长较快,能源形势比较严峻;能源结构不合理,可再生能源开发利用不充分。从技术成熟性和经济可行性看,风电在可再生能源中具有最好前景。近十几年来其发电成本已得到大幅下降,风电己具有与传统常规电源发电竞争的潜力。随着我国能源结构的调整,无污染可再生的风电日益得到重视。风电场功率预测一直是风电研究热点和技术必需。     

Efficient disparity vector prediction schemes with modified P frame for 2D camera arrays

An efficient disparity estimation algorithm for multi-view video sequences, recorded by a two-dimensional camera array in which the cameras are spaced equidistantly, is presented. Because of the strong geometrical relationship among views, the disparity vectors of a certain view can for most blocks be derived from the disparity vectors of other views. A frame constructed using that idea is called a D frame in this work. Three new prediction schemes which contain D frames are proposed for encoding 5 × 3 multi-view video sequences. The schemes are applied to several multi-view image sequences taken from a camera-array and they are compared in terms of quality, bit-rate and complexity. The experimental results show that the proposed prediction schemes significantly decrease the complexity of the encoder at a very low cost of quality and/or bit-rate.     

Detection of transcoded HEVC videos based on in-loop filtering and PU partitioning analyses

With the increasing maturity of video editing technology, forgers are more inclined to transcode videos to High Efficiency Video Coding (HEVC) videos, as HEVC not only enables people to enjoy high-definition videos but also allows broadcasters to stream it more efficiently across networks. Therefore, to verify the originality and authenticity, it is of great significance to propose an algorithm for detecting transcoded HEVC videos. In this paper, a theoretical model of video transcoding is first constructed, and a novel transcoding detection algorithm based on In-loop Filtering and Prediction Units (PU) Partition (IFPP) is proposed. By analyzing the statistical characteristics of strong and normal filtering modes in deblocking filtering and calculating offset values in Sample Adaptive Offset (SAO) filtering, the transcoding traces in inter-coded frames can be captured. In addition, PU partition statistics are also extracted to make full use of traces in intra-coded frames. By fusing these subfeatures, the proposed IFPP feature with 17 dimensions can be obtained, which is further fed to the Support Vector Machine (SVM) classifier. Finally, experiments are conducted on datasets with various coding parameters. Results show that the proposed algorithm outperforms existing algorithms and has better robustness.     

红外成像在预警机中的应用

红外成像系统以其在战术上的独特优势,成为现代军事空间预警系统的重要设备。本文就第一代通用组件,第二代高性能焦平面阵列成像系统在预警机中的应用,作了较为详尽的评述。     

3G移动通信系统中的新型宽带语音编码VMR-WB

本文介绍了一种将应用于第三代移动通信的新型语音声码器-变速率多模式宽带(VMR-WB)声码器。VMRWB 专为CDMA2000标准设计,有效语音带宽扩展为:50 Hz=7000 Hz,有四种不同速率的运行模式,每一种模式对应一定质量的平均数据速率。在相同的速率下,VMR-WB语音声码器的主观质量和性能较现有的窄带和宽带编码标准都有明显的提高。本文主要介绍其编码原理以及一些特性。     

嵌入式系统动态电源管理预测算法研究

针对目前在嵌入式系统中动态电源管理普遍采用超时算法节能效率低的缺点,采用预测的方法进行动态电源管理.提出一个动态电源管理预测算法,该算法通过利用设备空闲状态的历史信息对未来的空闲时间进行预测,预测结果作为动态电源管理的依据.实验结果说明该算法对工作状态平稳的系统空闲预测效果比较理想,适用于动态电源管理.     

An efficient reversible data hiding scheme using prediction and optimal side information selection

In this paper, we present an efficient histogram shifting (HS) based reversible data hiding scheme for copyright protection of multimedia. Firstly, an improved HS based multi-layer embedding process for rhombus prediction is employed by introducing a control parameter to explore the correlation of prediction errors. A rate-distortion model for HS embedding is then developed for optimal side information selection, which is especially suitable for low payload reversible data hiding when only a single layer embedding is required. Finally, a modified location map is constructed to facilitate the compression of location map and further increase the embedding capacity. Compared with similar schemes, experimental results demonstrate the superior performance of the proposed scheme in the terms of embedding capacity and stego-image quality.     

Comparison of energy intake prediction algorithms for systems powered by photovoltaic harvesters

Small size photovoltaic modules can harvest enough energy to power many personal devices and wireless sensor nodes. The prediction of solar energy intake is possible thanks to the periodical availability of the sunlight and its cyclic behavior. Thus, smart and innovative power management strategies can take advantage from intake prediction algorithms to optimize the energy usage by keeping the system in low power state as long as possible. On the other hand, very accurate predictions need time and energy because of complex calculations, thus an algorithm that can provide the optimal trade-off between computational effort and accuracy is a breakthrough for systems with tight power constraints. In this paper we introduce an innovative, efficient and reliable solar prediction algorithm, the weather conditioned moving average (WCMA). The algorithm has been further enhanced to increase performance using a phase displacement regulator (PDR) which reduces the average error to less than 9.2% at a minimum energy cost. The proposed new algorithm compares favorably with several competing approaches.     

Adaptive lossless compression of skeleton sequences

The increasing importance of skeleton information in surveillance big data feature analysis demands significant storage space. The development of an effective and efficient solution for storage is still a challenging task. In this paper, we propose a new framework for the lossless compression of skeleton sequences by exploiting both spatial and temporal prediction and coding redundancies. Firstly, we propose a set of skeleton prediction modes, namely, spatial differential-based, motion vector-based, relative motion vector-based, and trajectory-based skeleton prediction mode. These modes can effectively handle both spatial and temporal redundancies present in the skeleton sequences. Secondly, we further enhance performance by introducing a novel approach to handle coding redundancy. Our proposed scheme is able to significantly reduce the size of skeleton data while maintaining exactly the same skeleton quality due to lossless compression approach. Experiments are conducted on standard surveillance and Posetrack action datasets containing challenging test skeleton sequences. Our method obviously outperforms the traditional direct coding methods by providing an average of 73% and 66% bit-savings on the two datasets.