Reconstruction of multi-view compressed imaging using weighted total variation

This paper concentrates on the problem of image reconstruction from compressed sensing (CS) measurements in multi-view compressed imaging systems, where each view is acquired independently by CS technique. In order to take advantage of both the inter-view correlation and the spatial prior information in multi-view image sets, a weighted total variation (TV) regularized model, which combines the TV norm of a target view and the TV norm of the corresponding residual, is proposed. To efficiently solve the weighted TV regularization constrained problem, novel algorithms are presented for both the anisotropy TV and the isotropy TV cases. Given the multi-view CS measurements, a sliding window-based recovery framework is also developed to work with the weighted TV-based reconstruction algorithms and produce high-quality results. We show by experiments that the proposed methods greatly outperform the straight forward reconstruction which applies view by view image reconstruction independently, and also have significant advantages over other benchmark methods.     

Probabilistic pseudo-morphology for grayscale and color images

Mathematical morphology offers popular image processing tools, successfully used for binary and grayscale images. Recently, its extension to color images has become of interest and several approaches were proposed. Due to various issues arising from the vectorial nature of the data, none of them imposed as a generally valid solution. We propose a probabilistic pseudo-morphological approach, by estimating two pseudo-extrema based on Chebyshev inequality. The framework embeds a parameter which allows controlling the linear versus non-linear behavior of the probabilistic pseudo-morphological operators. We compare our approach for grayscale images with the classical morphology and we emphasize the impact of this parameter on the results. Then, we extend the approach to color images, using principal component analysis. As validation criteria, we use the estimation of the color fractal dimension, color textured image segmentation and color texture classification. Furthermore, we compare our proposed method against two widely used approaches, one morphological and one pseudo-morphological.     

Implementation-aware selection of the custom instruction set for extensible processors

This paper presents an approach for incorporating the effect of various logic synthesis options and logic level implementations into the custom instruction (CI) selection for extensible processors. This effect translates into the availability of a piecewise continuous spectrum of delay versus area choices for each CI, which in turn influences the selection of the CI set that maximizes the speedup per area cost (SPA) metric. The effectiveness of the proposed approach is evaluated by applying it to several benchmarks and comparing the results with those of a conventional technique. We also apply the methodology to the existing serialization algorithms aimed at relaxing register file constraints in multi-cycle custom instruction design. The comparison shows considerable improvements in the speedup per area compared to the custom instruction selection algorithms under the same area-budget constraint.     

Semantic-based QoS management in cloud systems: Current status and future challenges

Cloud Computing and Service Oriented Architectures have seen a dramatic increase of the amount of applications, services, management platforms, data, etc. gaining momentum for the necessity of new complex methods and techniques to deal with the vast heterogeneity of data sources or services. In this sense Quality of Service (QoS) seeks for providing an intelligent environment of self-management components based on domain knowledge in which cloud components can be optimized easing the transition to an advanced governance environment. On the other hand, semantics and ontologies have emerged to afford a common and standard data model that eases the interoperability, integration and monitoring of knowledge-based systems. Taking into account the necessity of an interoperable and intelligent system to manage QoS in cloud-based systems and the emerging application of semantics in different domains, this paper reviews the main approaches for semantic-based QoS management as well as the principal methods, techniques and standards for processing and exploiting diverse data providing advanced real-time monitoring services. A semantic-based framework for QoS management is also outlined taking advantage of semantic technologies and distributed datastream processing techniques. Finally a discussion of existing efforts and challenges is also provided to suggest future directions.     

一种非对称多核SDR的任务调度和分配算法

针对软件无线电(SDR)应用同步数据流的特点,提出一种非对称多核SDR的任务调度和分配算法。该算法综合考虑任务之间的通信时间和任务固定流水,保证任务调度和分配的通用性和并行性。利用整数线性规划(ILP)方法对任务调度和分配进行建模,采用任务拆分方法优化调度和分配的结果,进一步提高任务调度和分配的执行效率。在目标SDR平台上实现IEEE 802.11a频偏估计处理的任务调度和分配,实验结果表明,该算法能提高5.97%的软件无线电平台吞吐量和3.03%的处理器核平均利用率,并减少34.31%的处理器核最长空闲等待时间。     

基于RS232串行数据采集实现串口通信的收发系统

随着人类社会的发展,利用计算机设备实现生产过程的自动化成为提高生产力、减轻劳动强度的有效手段。由于大量设备的使用,必须随时了解实际情况,因此要对实时工作进行监视,并通过计算机辅助数据采集过程实现对数据的自动处理,并获得有关信息实现实时监控和串口通信过程。     

瑞利激光雷达探测中层大气密度和温度

利用瑞利（Rayleigh）散射激光雷达探测中层大气密度和温度的原理和方法,能够探测30~90 km范围的中层大气密度和温度的垂直分布。根据这种方法和实际测量得到的数据,把反演得到的结果与标准大气模型CI-RA86观测结果进行了对比,凸显具有较好的一致性。在一般情况下,30~65 km高度范围内激光雷达获得的大气密度与CIRA86密度偏差≤5%;温度偏差〈3 k,而在75 km以上温度偏差较大。     

雨雾天气下混合FSO/RF系统性能研究

通过对混合FSO/RF系统雨、雾天气下的误码率进行研究,从仿真结果中分析出雾是影响FSO系统的最主要因素,得出RF系统可以弥补FSO链路雾天缺陷的结论。经分析对比出雨天对FSO系统的影响要远小于雾天对FSO系统的影响。同时还对雨、雾天气情况下的开关键控（OOK）和脉冲相位调制（PPM）的性能进行了仿真分析。验证了在无线光通信系统中,PPM调制系统性能要优于OOK调制系统的性能。     

TH-PPM UWB通信系统多址性能研究

介绍了TH-PPM UWB信号,在AWGN信道和多用户干扰条件下对系统的性能进行了分析,包括误码率分析和系统所能接入的最大用户数,对其误码率进行了仿真.结果表明,随着接入用户数目的增加,系统误码率也增加,而增大重复码长度和脉冲重复时间则可降低系统误码率,但增加脉冲重复时间会降低信息传输速率.     

非理想信道条件下天线选择系统的SER性能分析

针对一般的相关检测天线选择系统,分析了Rayleigh衰落信道接收端非理想信道状态信息下发送天线选择(AS)系统的误符号率(SER)性能,给出了数值积分形式的理论表达式。仿真结果表明,无论在理想或有误差的信道信息下,理论结果与实际的仿真结果都保持了一致。数值分析结果表明在低信噪比(SNR)区域提高信道状态信息的准确程度比增加天线数目更能提高天线选择系统的性能。