为估计利用各类成像传感器自然获取图像的无损压缩极限，提出一个利用多尺度条件熵和记忆性度量的实用方法。
Lossless compression bounds of images naturally acquired by various imaging sensors are estimated using a practical method based on multi scale conditional entropy and memory measurement.
多传感器信息融合是信息学科的重要研究方向，本文的目的就是对分布在多个尺度上的传感器信息进行融合。
Multisensor fusion is an important research area in information subject, and the purpose of this paper is to fuse the multi-sensor information that is distributed at multiscale.
讨论了基于多尺度主元分析的故障传感器数据重构问题。
Multi-Scale Principal Component Analysis for data reconstruction of the faulty sensor is discussed.
基于多传感器单模型动态系统的多尺度估计理论，研究了不同尺度上拥有不同统计特性的多尺度融合算法及多尺度分布式融合估计算法。
Basing multiscale estimation theory of multi-sensors and single-model of dynamic system, the multiscale fuse algorithm and multiscale distribute fuse algorithm were studied respectively.
使用搭载翼型剪切流传感器的海洋湍流垂直剖面仪进行测量，是当前最普遍、最有效的获取海洋垂直剖面微尺度湍流数据的方法。
Now, the most universal and effectual method that used to get shearing data from the Marine vertical profiling is using vertical profilers associate with airfoil probes.
利用小波变换得到传感器信号在各个尺度上的系数，然后根据尺度系数矩阵建立主元分析模型进行传感器故障诊断。
Wavelet transform was utilized to get coefficients of each scale. Based the coefficient matrix, principal component analysis model was established to diagnose sensor fault.
此外，本文也研究了传感器的敏感机理和硅微皮拉尼传感器中气体导热的微尺度效应。
Moreover, the sensing mechanism of the Pirani sensor and the micro-scale thermal conduction of the gas in the silicon-based Pirani sensor have also been investigated in this work.
纳米光纤探针作为近场光学显微镜和纳米光纤生物传感器中的关键元件，用于微小尺度物体的检测和分析。
Fiber-optical nanoprobes are the key elements for detecting and analyzing micro-scale objects in near-field optical microscopes and fiber-optical nano-biosensors.
纳米光纤探针作为近场光学显微镜和纳米光纤生物传感器中的关键元件，用于微小尺度物体的检测和分析。
Fiber-optical nanoprobes are the key elements for detecting and analyzing micro-scale objects in near-field optical microscopes and fiber-optical nano-biosensors.
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