基于独立分量分析的多分辨率遥感图像融合算法

研究了目前常用的遥感图像融合方法,提出了基于独立分量分析的多分辨率遥感图像融合方法,分析了用于独立分量分析的目标函数（如峭度、近似负熵和互信息）,给出了独立分量分析的优化快速算法,并详细描述了提取源信息独立分量的具体步骤。最后,将独立分量分析法应用于高分辨率光学图像和低分辨率光学图像的融合,与采用主分量分析法融合的图像相比,图像质量得到很大的提高。     

一种新颖的统一混沌保密通信系统

文章详细地介绍了统一混沌系统和Pecora-Carroll同步法,用P-C法实现统一混沌系统同步,提出了一种新颖的保密通信系统,并用Matlab6.5/Simulink仿真软件进行建模仿真。结果表明,该系统能够正确地解调出原始加密信号,达到保密通信的目的。     

QoS-aware routing in emerging heterogeneous wireless networks[Quality-of-Service-Based Routing Algorithms for Heterogeneous Networks]

The integration of different kinds of wireless mobile networks, or heterogeneous wireless networks (HWNs), is emerging. However, a systematic discussion with regard to the special requirements and the complexity of QoS-aware routing in such networks and how QoS is blended with routing is still largely missing. This article aims to cast some light on these aspects. Based on an analysis of the basic architecture of an emerging heterogeneous wireless network and its new requirements on QoS-aware routing, a policy-based QoS supporting system infrastructure and a QoS-aware routing algorithm called QRA are presented in this article. The presentation is specifically given to these issues and components that are unique to HWNs and its QoS routing. The evaluation results show the impact of different network parameters on the performance of QoS-aware routing in HWNs     

On the Feedback Capacity of Power-Constrained Gaussian Noise Channels With Memory

For a stationary additive Gaussian-noise channel with a rational noise power spectrum of a finite-order L, we derive two new results for the feedback capacity under an average channel input power constraint. First, we show that a very simple feedback-dependent Gauss-Markov source achieves the feedback capacity, and that Kalman-Bucy filtering is optimal for processing the feedback. Based on these results, we develop a new method for optimizing the channel inputs for achieving the Cover-Pombra block-length- n feedback capacity by using a dynamic programming approach that decomposes the computation into n sequentially identical optimization problems where each stage involves optimizing O(L ²) variables. Second, we derive the explicit maximal information rate for stationary feedback-dependent sources. In general, evaluating the maximal information rate for stationary sources requires solving only a few equations by simple nonlinear programming. For first-order autoregressive and/or moving average (ARMA) noise channels, this optimization admits a closed-form maximal information rate formula. The maximal information rate for stationary sources is a lower bound on the feedback capacity, and it equals the feedback capacity if the long-standing conjecture, that stationary sources achieve the feedback capacity, holds     

Noncoherent Ultra-Wideband (De)Modulation

Ultra-wideband (UWB) radios have received increasing attention recently for their potential to overlay legacy systems, their low-power consumption and low-complexity implementation. Because of the pulsed or duty-cycled nature of the ultra-short transmitted waveforms, timing synchronization and channel estimation pose major, and often conflicting, challenges and requirements. In order to address (or in fact bypass) both tasks, we design and test noncoherent UWB (de)modulation schemes, which remain operational even without timing and channel information. Relying on integrate-and-dump operations of what we term "dirty templates," we first derive a maximum likelihood (ML) optimal noncoherent UWB demodulator. We further establish a conditional ML demodulator with lower complexity. Analysis and simulations show that both can also be applied after (possibly imperfect) timing acquisition. Under the assumption of perfect timing, our noncoherent UWB scheme reduces to a differential UWB system. Our approach can also be adapted to a transmitted reference (TR) UWB system. We show that the resultant robust-to-timing TR (RTTR) approach considerably improves performance of the original TR system in the presence of timing offsets or residual timing acquisition errors     

量子链和量子点光学特性的比较研究

比较研究了InGaAs/GaAs量子链和量子点的稳态和瞬态光学特性.实验发现,量子链的荧光寿命有很强的探测能量依赖关系,而量子点的荧光寿命随能量变化较小;量子链的荧光寿命随着激发功率迅速增加,高功率时趋于饱和,而量子点的荧光寿命随激发功率变化缓慢;此外,量子链样品的荧光上升时间也比量子点的小得多.这些结果清楚表明,在量子链结构中,参与发光的载流子之间存在很强的耦合和输运.进一步分析表明,这种耦合作用主要发生在量子链方向.荧光的偏振特性进一步证实了这一点.     

部分耗尽SOI MOSFETs中沟道的非对称掺杂效应

利用二维模拟软件对部分耗尽SoI器件中的非对称掺杂沟道效应进行了模拟.详细地研究了该结构器件的电学性能,如输出特性,击穿特性.通过本文模拟发现部分耗尽SOI非对称掺杂沟道相比传统的部分耗尽SOI,能抑制浮体效应,改善器件的击穿特性.同时跟已有的全耗尽SOI非对称掺杂器件相比,部分耗尽器件性能随参数变化,在工业应用上具有可预见性和可操作性.因为全耗尽器件具有非常薄的硅膜,而这将引起如前栅极跟背栅极的耦合效应和热电子退化等寄生效应.     

Nonrigid registration of 3-d multichannel microscopy images of cell nuclei.

We present an intensity-based nonrigid registration approach for the normalization of 3-D multichannel microscopy images of cell nuclei. A main problem with cell nuclei images is that the intensity structure of different nuclei differs very much; thus, an intensity-based registration scheme cannot be used directly. Instead, we first perform a segmentation of the images from the cell nucleus channel, smooth the resulting images by a Gaussian filter, and then apply an intensity-based registration algorithm. The obtained transformation is applied to the images from the nucleus channel as well as to the images from the other channels. To improve the convergence rate of the algorithm, we propose an adaptive step length optimization scheme and also employ a multiresolution scheme. Our approach has been successfully applied using 2-D cell-like synthetic images, 3-D phantom images as well as 3-D multichannel microscopy images representing different chromosome territories and gene regions. We also describe an extension of our approach, which is applied for the registration of 3D + t (4-D) image series of moving cell nuclei.     

一个用于高速信号传输的对PVT变化不敏感的低功耗锁相环

介绍了一个用于高速信号传输的低功耗锁相环. 提出了一种新的开环校准方法. 该校准通过上电时候进行的开环数字校准很大程度上减轻了工艺变化对电路的影响,相比以前的闭环校准方法,该方法可以显著缩短校准时间. 在这个锁相环中采用了双环路的结构来获得对工艺、温度和环境变化不敏感的环路参数：例如衰减因子、相位裕度等. 还设计了一种新的鉴频鉴相器,它内嵌了电平转换的功能,简化了电路. 该PLL的设计通过小心的供电网络划分来降低电源噪声的耦合. 设计的锁相环路在输出为1.6GHz的时候均方根抖动为3.1ps,而仅消耗约为1mA的电流.     

Single-Image Super-Resolution Reconstruction via Learned Geometric Dictionaries and Clustered Sparse Coding

Recently, single image super-resolution reconstruction (SISR) via sparse coding has attracted increasing interest. In this paper, we proposed a multiple-geometric-dictionaries-based clustered sparse coding scheme for SISR. Firstly, a large number of high-resolution (HR) image patches are randomly extracted from a set of example training images and clustered into several groups of "geometric patches," from which the corresponding "geometric dictionaries" are learned to further sparsely code each local patch in a low-resolution image. A clustering aggregation is performed on the HR patches recovered by different dictionaries, followed by a subsequent patch aggregation to estimate the HR image. Considering that there are often many repetitive image structures in an image, we add a self-similarity constraint on the recovered image in patch aggregation to reveal new features and details. Finally, the HR residual image is estimated by the proposed recovery method and compensated to better preserve the subtle details of the images. Some experiments test the proposed method on natural images, and the results show that the proposed method outperforms its counterparts in both visual fidelity and numerical measures.