基于半像素错位的多幅图像重建高分辨率图像技术研究

介绍了一种基于半像素错位的多幅图像重建高分辨率图像技术。分析了半像素错位的多幅图像与高分辨率图像各像素灰度值的对应关系 ,并从CCD数字化采样的角度进行了论证。同时 ,结合实际摄像机CCD结构 ,求出了高分辨率图像重建的计算公式 ,并通过实验进行了验证和完善。重建的本质是以原高分辨率图像的 4邻域平均图像为基础 ,增加一定比例的边缘细节信息 ,去接近原高分辨率图像。CCD的动态范围越大 ,图像的灰度级越多 ,那么计算误差就越小 ,图像的边缘细节信息就可以利用更多 ,重建的图像就越接近原高分辨率图像。通过实验和分析表明 ,利用半像素错位的多幅低分辨率图像重建高分辨率图像的原理是正确的 ,方案是可行的     

Moderate and Small Deviations for the Ranges of One-Dimensional Random Walks

We establish moderate and small deviations for the ranges of integer valued random walks. Our theorems apply to the limsup and the liminf laws of the iterated logarithm. We establish moderate and small deviations for the ranges of integer valued random walks. Our theorems apply to the limsup and the liminf laws of the iterated logarithm.     

A One‐Kilobit PQR‐CMOS Smart Pixel Array

The photonic quantum ring (PQR) laser is a three dimensional whispering gallery (WG) mode laser and has anomalous quantum wire properties, such as microampere to nanoampere range threshold currents and √T‐dependent thermal red shifts. We observed uniform bottom emissions from a 1‐kb smart pixel chip of a 32×32 InGaAs PQR laser array flip‐chip bonded to a 0.35 µm CMOS‐based PQR laser driver. The PQR‐CMOS smart pixel array, now operating at 30 MHz, will be improved to the GHz frequency range through device and circuit optimization.     

更新时间概率模型及其无偏估计定理的论证

本文提出应用小参数法 ,探讨 Markov链中相邻两次更新时刻内稀疏事件的概率估计问题 .建立了三种最重要的具有更新时间的概率模型 .通过小参数的引入和对概率式的幂展开 ,进而推证出幂渐近展开系数的模型估算法 .论证了无偏估计的重要定理 ,给出了概率估计式和无偏估计精度 .亦将许多算法扩展到Markov链的任意状态空间     

Functional Quantization and Small Ball Probabilities for Gaussian Processes

Quantization consists in studying the L ^r -error induced by the approximation of a random vector X by a vector (quantized version) taking a finite number n of values. We investigate this problem for Gaussian random vectors in an infinite dimensional Banach space and in particular, for Gaussian processes. A precise link proved by Fehringer⁽⁴⁾ and Dereich et al. ⁽³⁾ relates lower and upper bounds for small ball probabilities with upper and lower bounds for the quantization error, respectively. We establish a complete relationship by showing that the same holds for the direction from the quantization error to small ball probabilities. This allows us to compute the exact rate of convergence to zero of the minimal L ^r -quantization error from logarithmic small ball asymptotics and vice versa.     

同步辐射小角x射线散射方法研究由城市固体垃圾制备的活性炭

应用同步辐射小角x射线散射方法研究了由不同城市固体垃圾制备而成的活性炭的孔结构-结果发现利用木类、纸张、塑料这三类典型垃圾组分的热解残余物为原料制备中孔发达的活性炭是可行的-活性炭的形态和结构取决于垃圾热解残余物的组分和热解程度等因素- 关键词： 小角x射线散射 活性炭 分形维数 平均孔径     

Analysis of blockwise shrinkage wavelet estimates via lower bounds for no-signal setting

A blockwise shrinkage is a popular procedure of adaptation that has allowed the statisticians to establish an impressive bouquet of asymptotic mathematical results and develop softwares for solving practical problems. Traditionally risks of the estimates are studied via upper bounds that imply sufficient conditions for a blockwise shrinkage procedure to be minimax. This article suggests to analyze the estimates via exact (non-asymptotic) lower bounds established for a no-signal setting. The approach complements the familiar minimax, Bayesian and numerical analysis, it allows to find necessary conditions for a procedure to attain desired rates, and it sheds a new light on popular choices of blocks and thresholds recommended in the literature. Mathematical results are complemented by a numerical study. Supported in part by NSF Grants DMS-9971051 and DMS-0243606.     

罗氏沼虾幼苗体内一种极小病毒的序列测定与分析

从患罗氏沼虾幼苗肌肉白浊病的幼虾体内分离到两种病毒颗粒,诺达病毒(MrNV)和直径只有15nm的小病毒颗粒(extrasmallvirus,XSV),本文通过建立病毒cDNA文库获得XSV基因组的部分序列,在此基础上合成探针,用从病虾组织中提取的总PNA进行Northern杂交,结果表明XSV基因组至少包括两条RNA片段.利用不同的方法对XSV的两端序列进行克隆和测定,分别得到了872、831和662bp3个相互重叠的序列片段,这3个序列的阅读框编码一个相同的大小在17×103左右的蛋白.     

变参数波振器中小信号增益公式

利用微扰展开技术推导出变参数波振器的小信号增益两个近似求积表达式并将其计算结果与数值模拟结果进行了比较,二者吻合很好。利用近似解析式对小信号增益进行了初步探讨,得到了电子入射能量可低于初始谐振能,能散度允许范围受波振器设计影响以及降低锥度改变率可提高小信号增益等新结论。     

Simple Constructions of Almost k-wise Independent Random Variables

We present three alternative simple constructions of small probability spaces on n bits for which any k bits are almost independent. The number of bits used to specify a point in the sample space is (2 + o(1)) (log log n + k/2 + log k + log 1/?), where ? is the statistical difference between the distribution induced on any k bit locations and the uniform distribution. This is asymptotically comparable to the construction recently presented by Naor and Naor (our size bound is better as long as ? < 1/(k log n)). An additional advantage of our constructions is their simplicity.