Sampled data systems

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  • From its title, you can see that this book is about real-time (computing, communication, and information) systems. Rather than pausing here to define the term precisely, which we will do in Chapter 2, let us just say for now that a real-time system is required to complete its work and deliver its services on a timely basis. Examples of real-time systems include digital

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  • Thus far we have discussed how to control continuous-time systems for both state-feedback and output-feedback problems. With today’s high performance real-time systems, the control algorithms developed in the continuous-time framework are typically implemented on a sampled-data system. As long as the sampling rate of the controller is high with

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  • An empirical study of scale economies in the Chinese Railway System Although results are not presented here, I have estimated several additional specifications of the basic empirical test. The absence of a positive choice effect does not seem to derive from the particular weighting of the data used here—one might prefer to weight MSAs equally, or by the number of SAT-takers, rather than by their high-school-age populations—nor from the inclusion in the sample of schools with too few SAT-takers to permit accurate estimation of the school mean...

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  • The scripts provided as part of this paper are sample code which can be used to base your own scripts on. These scripts have been tested on an Oracle Enterprise Linux - 2 node cluster. It is expected that they should work on all Oracle Clusterware supported platforms. Oracle Support cannot provide any direct support for these scripts. You should thoroughly test the scripts – in particular the check action of each script to ensure compatibility with your operating system.

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  • SAMPLING AND RECONSTRUCTION WITH INTERSAMPLE ERROR A fundamental requirement of sampled-data systems is the sampling of continuoustime signals to obtain a representative set of numbers that can be used by a digital computer. The primary goal of this chapter is to provide an understanding of this process. The first section explores theoretical aspects of sampling and the formal considerations of signal recovery, including ideal Wiener filtering in signal interpolation. Aliasing of signal and noise are considered next in a detailed development involving a heterodyne basis of evaluation. ...

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  • Internal audit technologies can greatly improve the efficiency, quality and consistency of the audit process. Data analysis software can also enhance the audit by allowing the computerised testing of entire populations of data as opposed to relying on detail testing of sample data. Internal audit infrastructure and methodologies can be developed internally or acquired from a third party. PricewaterhouseCoopers, for example, offers the TeamMate™, an integrated electronic working paper software application designed specifically for internal auditors.

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  • The Natural Language Understanding Engine Test Environment (ETE) is a GUI software tool that aids in the development and maintenance of large, modular, natural language understanding (NLU) systems. Natural language understanding systems are composed of modules (such as partof-speech taggers, parsers and semantic analyzers) which are difficult to test individually because of the complexity of their output data structures.

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  • The reader is provided with information on how to choose between the techniques and how to design a system that takes advantage of the best features of each of them. Imminently practical in approach, the book covers sampled data systems, choosing A-to-D and D-to-A converters for DSP applications, fast Fourier transforms, digital filters, selecting DSP hardware, interfacing to DSP chips, and hardware design techniques. It contains a number of application designs with thorough explanations.

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  • This document describes the tasks to install Oracle Database 10g Standard Edition on a Windows two-node cluster, using Real Application Clusters (RAC) and Automated Storage Management (ASM). This install also builds a general purpose starter database with the Sample Schemas included and with automatic disk backup enabled.

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  • This self-study course is organized into subject matter areas, each containing learning objectives to help you determine what you should learn along with text and illustrations to help you understand the information. The subject matter reflects day-to-day requirements and experiences of personnel in the rating or skill area.

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  • In recent years many successful machine learning applications have been developed, ranging from data mining programs that learn to detect fraudulent credit card transactions, to information filtering systems that learn user’s reading preferences, to autonomous vehicles that learn to drive on public highways. At the same time, machine learning techniques such as rule induction, neural networks, genetic learning, case-based reasoning, and analytic learning have been widely applied to real-world problems.

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  • Modeling Hydrologic Change: Statistical Methods is about modeling systems where change has affected data that will be used to calibrate and test models of the systems and where models will be used to forecast system responses after change occurs. The focus is not on the hydrology. Instead, hydrology serves as the discipline from which the applications are drawn to illustrate the principles of modeling and the detection of change. All four elements of the modeling process are discussed: conceptualization, formulation, calibration, and verification.

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  • “There is no such thing as an easy experiment, nor is there any substitute for careful experimentation in many areas of basic research and applied product development.” From Experimental Methods for Engineers by J. P. Holman Measurement is a multidisciplinary experimental science. Measurement systems synergistically blend science, engineering and statistical methods to provide fundamental data for research, design and development, control of processes and operations, and facilitate safe and economic performance of systems.

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  • Transforming the information source to a form compatible with a digital system. Sampling. Aliasing. Quantization Uniform and non-uniform. Baseband modulation. Binary pulse modulation. M-ary pulse modulation. M-PAM (M-ary Pulse amplitude modulation).Assuming real time transmission and equal energy per transmission data bit for binary-PAM and 4-ary PAM

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  • The mutual fund data come from the 1998 CRSP Survivor Bias FreeMutual Fund Database. Our initial sample contains 2,609 domestic equity mutual funds. We exclude multiple share classes for the same fund as well as funds with only a year or less of available returns. The initial sample is used to obtain the values of the prior parameters in the empirical Bayes pro- cedure mentioned previously.

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  • A 1992 study conducted by Arthur Andersen , commissioned by the Associated Credit Bureaus (now known as the Consumer Data Industry Association) used a different methodology to conclude that the error rate was much lower. This study reviewed the behavior of 15,703 consumers who were denied credit based on a credit grantor’ s scoring system. From this sample, 1,223 consumers (7.8%) requested their credit report from the issuing credit repository, and 304 consumers (1.9% of the total sample) disputed the information on the report. Of these, 36 disputes (11.

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  • The survey is designed to solicit input from those in the field of construction and project management concerning leadership and the leadership skills. Questions centered on the importance of leadership, the kinds of leadership skills people should pursue, and the most-commonly used skills. A common survey process includes defining the survey objectives, developing a sample frame, specifying the strategy for data collection, and conducting the appropriate analyses.

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  • Molecular markers present numerous advantages over conventional phenotype based alternatives.

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  • As our goal is to observe managers’ abilities to generate profits through active management, we employ only properties that were both bought and sold within the sample period, and thus for which we have round trip transaction returns. In future versions of the paper, we will relax this condition where possible to account for properties purchased within the sample period and not yet sold, as well as properties purchased prior to the start of the sample and sold with the sample period.

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  • The following pages are devoted to a statistical analysis of the principal factors affecting credit risk. The information on which the study is based was obtained from a sample of 2,765 applications of persons to whom loans were granted. The data, secured through the cooperation of 21 large banks operating personal loan departments in 16 cities situated in ii states,1 are presented in a series of tables giving the distri- butions of good and of bad loans according to the several risk factors selected.

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