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Three different methods are presented to subtract thermal drifts and low-frequency noise from the signal of infrared array. The first is dead pixels with open Indium bumps, the second is reference output as implemented on the Hawaii2 multiplexer, and the third is dark pixels to emulate reference cells having a capacity connected to the gate of the unit cell field-effect transistor (FET). The third method is the most effective and yields a reduction in readout noise from15.4–9.4 erms. A novel method will be described to extend this readout technique to the Aladdin 1 K × 1 K InSb array. This revised version was published online in July 2006 with corrections to the Cover Date.  相似文献   
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1Water LossInitiativesUnaccounted-for water(or unbilled water)has beenreceiving newscrutiny at both the state and nationallevels.For years,water conservationeffortsin Europehave emphasized reduction in water loss to a muchgreater extent thaninthe United S…  相似文献   
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One of the first operations in a seismic signal processing system applied to earthquake data is to distinguish between valid and invalid records. Since valid signals are characterized by a combination of their time and frequency properties, wavelets are natural candidates for describing seismic features in a compact way. This paper develops a seismic buffer pattern recognition technique, comprising wavelet-based feature extraction, feature selection based on the mutual information criterion, and neural classification based on feedforward networks. The ability of the wavelet transform to capture discriminating information from seismic data in a small number of features is compared with alternative feature reduction techniques, including statistical moments. Three different variations of the wavelet transform are used to extract features: the discrete wavelet transform, the single wavelet transform and the continuous wavelet transform. The mutual information criterion is employed to select a relatively small set of wavelets from the time–frequency grid. Firstly, it is determined whether wavelets can capture more informative data in an equal number of features compared with other features derived from raw data. Secondly, wavelet-based features are compared with features selected based on prior knowledge of class differences. Thirdly, a technique is developed to optimize wavelet features as part of the neural network training process, by using the wavelet neural network architecture. The automated classification techniques developed in this paper are shown to perform similarly to human operators trained for this function. Wavelet-based techniques are found to be useful, both for preprocessing of the raw data and for extracting features from the data. It is demonstrated that the definition of wavelet features can be optimized using the classification wavelet network architecture.  相似文献   
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Throughgoing fractures play a major role in subsurface fluid flow yet the kinematics of their formation, which directly impact rock flow properties, are often difficult to establish. We investigate throughgoing fractures in the Monterey Formation of California that developed by the coalescence of pre-existing joints. At Lompoc Landing, throughgoing fractures fall into three main groups: linked, linked with aperture, and breccia zones. The segmented nature of their walls provides numerous piercing points to firmly establish the sense of displacement. Analysis of displacement vectors derived from piercing points demonstrates that the NW–SE trending throughgoing fractures, often interpreted as strike–slip faults, are in fact extensional structures in origin. We suggest that this method may be applied to throughgoing fractures that form by the same mechanism in other geologic settings. Establishing kinematics of throughgoing fractures will lead to a better understanding of their contribution to subsurface fluid flow.  相似文献   
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