Scalable Network Coding for Heterogeneous Devices over Embedded Fields

In complex network environments, there always exist heterogeneous devices with different computational powers. In this work, we propose a novel scalable random linear network coding (RLNC) framework based on embedded fields, so as to endow heterogeneous receivers with different decoding capabilities. In this framework, the source linearly combines the original packets over embedded fields based on a precoding matrix and then encodes the precoded packets over GF(2) before transmission to the network. After justifying the arithmetic compatibility over different finite fields in the encoding process, we derive a sufficient and necessary condition for decodability over different fields. Moreover, we theoretically study the construction of an optimal precoding matrix in terms of decodability. The numerical analysis in classical wireless broadcast networks illustrates that the proposed scalable RLNC not only guarantees a better decoding compatibility over different fields compared with classical RLNC over a single field, but also outperforms Fulcrum RLNC in terms of a better decoding performance over GF(2). Moreover, we take the sparsity of the received binary coding vector into consideration, and demonstrate that for a large enough batch size, this sparsity does not affect the completion delay performance much in a wireless broadcast network.     

Low-Complexity Alternatives to the Optimal Linear Coding Scheme for Transmitting ARMA Sources

In the era of the Internet of Things, there are many applications where numerous devices are deployed to acquire information and send it to analyse the data and make informed decisions. In these applications, the power consumption and price of the devices are often an issue. In this work, analog coding schemes are considered, so that an ADC is not needed, allowing the size and power consumption of the devices to be reduced. In addition, linear and DFT-based transmission schemes are proposed, so that the complexity of the operations involved is lowered, thus reducing the requirements in terms of processing capacity and the price of the hardware. The proposed schemes are proved to be asymptotically optimal among the linear ones for WSS, MA, AR and ARMA sources.     

超分辨重建技术及其研究进展

超高分辨成像技术一直是航天、遥感、目标识别等领域的研究热点。随着光学成像到光电数字成像的转变,如何提高CCD的几何分辨率,已成为研制高分辨光电成像系统亟待解决的问题。本文从理论和工程实现的角度介绍了超分辨成像的技术原理,分析了实现超分辨重建技术的几种方法,主要描述了微扫描和亚像元两种重建技术的实现方式,指出了目前超分辨技术存在的缺陷。最后,针对超分辨技术中无混淆重建带宽较窄的问题,提出了一种新的技术方案。该方案将光学编码技术与目前的亚像元技术相结合,可将重建带宽拓展3倍。研究结论指出：融合了光学,光电子学和信号处理的成像系统的综合设计,将是未来成像领域的一个重要研究方向。     

近红外光谱小波分析在土壤参数预测中的应用

从田间采集了150个田间土壤样本,在分析了所有样本的土壤参数统计特征之后,对原始近红外光谱数据进行了聚类分析,分别得到了50个土壤全氮和50个土壤有机质的等价样本及其对应光谱。对样本光谱曲线进行8层Biorthogonal小波包分解,分解得到的最低低频[80]结点对应着土壤水分以及土壤质地的光谱变化趋势,最高高频[8 255]结点对应着土壤粒度、光谱仪精度等引起的高频震荡。对以上两个结点进行重构并从样本光谱曲线中剔除以上影响成分,得到了对应的土壤参数特征光谱。基于特征光谱建立了土壤参数偏最小二乘回归模型：全氮偏最小二乘预测模型的预测系数r_c达到了0.960,验证系数r_v达到了0.920;有机质偏最小二乘预测模型的预测系数r_c达到0.922,验证系数r_v达到0.883。模型精度明显提高,满足实际生产的需要。     

Wavelet-modified maximum average correlation height filter for out-of-plane rotation invariance

In this paper, we implement a wavelet-modified maximum average correlation height (WaveMACH) filter for recognition of 0-360° out-of-plane rotated targets employing hybrid digital-optical correlator architecture. A chirp function is used with the synthesized WaveMACH filter, which focuses the correlation signals in three different planes, thereby providing the choice of recording a single correlation peak at a particular plane. Signal-to-noise ratio and peak-to-sidelobe ratio have been calculated as metrics of goodness of the proposed WaveMACH filter.     

Orthonormal wavelets and shift invariant generalized multiresolution analyses

All wavelets can be associated to a multiresolution-like structure, i.e. an increasing sequence of subspaces of . We consider the interaction of a wavelet and the shift operator in terms of which of the subspaces in this multiresolution-like structure are invariant under the shift operator. This action defines the notion of the shift invariance property of order . In this paper we show that wavelets of all levels of shift invariance exist, first for the classic case of dilation by 2, and then for arbitrary integral dilation factors.

     

Deterministic quantum dense coding with cluster state in optical systems

We propose two optical schemes for implementing the deterministic single-particle and two-particle quantum dense coding using four-qubit cluster states. In the protocols, the photon is neuter particle, so it has longer decoherence time with the environment than other particles. It is easy to implement single-bit gate using the linear optical elements under certain conditions, so the transformations performed on the photons by Alice can be easily achieved. Here the cluster states can be exactly discriminated using the parity detector, PBS and FS-PBS. In addition, the success probabilities of the dense coding are both equal to 1.     

Solving diffusion equation using wavelet method

A wavelet-based numerical method based on wavelets of Hermite cubic splines is presented for computing singularly perturbed convection-dominated diffusion equation. The advantages of the method are explained. To improve the accuracy of singular areas, wavelets are configured hierarchically for solving algebraic equations. Numerical examples show that the proposed method has good efficiency and precision.