浅析多媒体数据压缩技术

文章介绍了数据压缩的必要性、可行性,数据压缩的概念、常用压缩方法和典型算法,并指出了数据压缩的广泛应用。     

光源编码的白光散斑剪切干涉计量术

本文提出了一种用非相干光源照明进行剪切干涉计量的方法—光源编码的白光散斑剪切干涉计量术.它采用光栅对光源进行编码以提高空间相干性,使物体的两个剪切像的波面部分相干叠加,以实现剪切干涉.     

人防车载警报器的软硬件设计

以AT89C52单片机为控制核心，设计了新颖、实用的车载式警报器。着重介绍了此警报器软硬件设计思想和具体实现电路。     

液晶空间光调制器在阿达玛变换光谱仪中的应用研究——快速精确的解码方法

研究了液晶空间光调制器(LC-SLM)作为固定不动的编码模板应用于阿达玛变换光谱仪(HTS),提出了快速精确的解码方法,给出了由液晶空间光调制器编码模板所带来的均方根信噪比的改善.     

光电跟踪系统轴角编码与数字显示

介绍一种光电跟踪系统所采用的轴角编码与数字显示器。分析跟踪型轴角编码器的基本原理，探讨并提出了提高分辨率的具体方法，保证系统测角精度并可进行数字显示。     

Quantum Bayesian computation

Quantum Bayesian computation is an emerging field that levers the computational gains available from quantum computers. They promise to provide an exponential speed-up in Bayesian computation. Our article adds to the literature in three ways. First, we describe how quantum von Neumann measurement provides quantum versions of popular machine learning algorithms such as Markov chain Monte Carlo and deep learning that are fundamental to Bayesian learning. Second, we describe quantum data encoding methods needed to implement quantum machine learning including the counterparts to traditional feature extraction and kernel embeddings methods. Third, we show how quantum algorithms naturally calculate Bayesian quantities of interest such as posterior distributions and marginal likelihoods. Our goal then is to show how quantum algorithms solve statistical machine learning problems. On the theoretical side, we provide quantum versions of high dimensional regression, Gaussian processes and stochastic gradient descent. On the empirical side, we apply a quantum FFT algorithm to Chicago house price data. Finally, we conclude with directions for future research.     

Photolithographic Encoding of Metal Complexes

A platform technology for the creation of spatially resolved surfaces encoded with a monolayer consisting of different metal complexes was developed. The concept entails the light‐triggered activation of a self‐ assembled monolayer (SAM) of UV‐labile anchors, that is, phenacylsulfides, and the subsequent cycloaddition of selected diene‐functionalized metal complexes at defined areas on the surface. The synthesis and characterization of the metal complexes for the UV‐light assisted anchoring on the surface and a detailed study of a short‐chain oligomer model system in solution confirm the high efficiency of the photoreaction. The hybrid materials obtained by this concept can potentially be utilized for the design of highly valuable catalytic or (opto‐)electronic devices.     

具有遗传性疾病和性状的遗传位点分析

随着信息技术的进步和发展,现代生物学越来越多地将这些技术用于大规模生物数据的收集、分析、挖掘等过程.大量计算机技术,特别是统计方法被用来进行复杂疾病的分析.大量研究表明,人体的许多表型性状差异以及对药物和疾病的易感性等都可能与某些位点相关联,或和包含有多个位点的基因相关联.因此,定位与性状或疾病相关联的位点在染色体或基因中的位置,能帮助研究人员了解性状和一些疾病的遗传机理,也能使人们对致病位点加以干预,防止一些遗传病的发生.利用随机森林方法、Bootstrap重抽样、logistic回归等大数据分析方法,意在解决优化生物学位点关联性分析中单一致病位点识别、多位点相互作用和多性状位点关联性分析等子问题.     

Signal enhancement of a novel multi-address coding lidar backscatters based on a combined technique of demodulation and wavelet de-noising

Multi-address coding (MAC) lidar is a novel lidar system recently developed by our laboratory. By applying a new combined technique of multi-address encoding, multiplexing and decoding, range resolution is effectively improved. In data processing, a signal enhancement method involving laser signal demodulation and wavelet de-noising in the downlink is proposed to improve the signal to noise ratio (SNR) of raw signal and the capability of remote application. In this paper, the working mechanism of MAC lidar is introduced and the implementation of encoding and decoding is also illustrated. We focus on the signal enhancement method and provide the mathematical model and analysis of an algorithm on the basis of the combined method of demodulation and wavelet de-noising. The experimental results and analysis demonstrate that the signal enhancement approach improves the SNR of raw data. Overall, compared with conventional lidar system, MAC lidar achieves a higher resolution and better de-noising performance in long-range detection.