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potential evapotranspiration The rate at which evapotranspiration (q.v.) would occur, given the ambient conditions of atmospheric temperature humidity and solar radiation, if there were no limit to the supply of water to the soil surface and/or to plants. potential recharge In ltrating waters passing below the root-suction base (q.v.). potential yield The yield of a commissioned source or group of water supply sources as constrained only by well and/or aquifer properties for speci ed conditions and demands. potentiometric surface A synonym of piezometric surface (q.v.). precipitation Rain, hail, sleet or snow. principle of electroneutrality The phenomenon that means water cannot carry a net electrical charge (positive or negative), but must always be electrically neutral. principle of superposition The principle that drawdown (q.v.) due to a number of wells pumping in consort equals the sum of the drawdowns each well would cause were it pumping alone. probabilistic modeling An approach to the application of a mathematical model in which all inputs and outputs are probability distributions, rather than single parameter values. protons Hydrogen ions (H+).

+ p(x)d(x, x) + (x) = 0. Setting log (x) = (x)/p(x), we obtain p(x) log q(x|x) + d(x, x) + log (x) = 0 q(x)

(9.140)

Three phase hand-shaking protocols in SPIN [25].

A couple of interesting options are available with mdfind. The onlyin option lets you limit the search to a specified directory. The live option keeps the query going, giving updated results if the metadata changes until you press Control-C to stop it.

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Theorem 15.2.3 Let A(n) denote the typical set for the probability mass function p(s1 , s2 , s3 ), and let

10.5 GENERALIZED SAMPLING REVISITED By this point in the text, it is assumed that the reader is familiar with diverse multiplex sampling schemes. The present section revisits three particular strategies in light of the lessons of the past several chapters. Our goal is to provide the system designer with a framework for comparative evaluation of coding and sampling strategy. An optical sensor may be evaluated based on physical (resolution, FOV, and depth of eld), signal delity (SNR and MSE), and information-theoretic (feature sensitivity and transinformation) metrics. While detailed discussion of the information theory of imaging is beyond the scope of this text, our approach in this section leans toward this perspective. We focus in particular on SVD analysis of measurement systems. As discussed in Section 8.4, the singular vectors of a measurement system represent the basic structure of sensed image components, and the singular values provide a measure of how many components are measured and the delity with which they can be estimated. When two different measurement strategies are used to estimate the same object features, SVD analysis provides a simple mechanism for comparison. Assuming similar detector noise characteristics, the system with the larger eigenvalue for estimating a particular component will achieve better performance in estimating that component. While joint design of coding, sampling, and image estimation algorithms is central to computational imager design, SVD analysis provides a basis for comparison that is relatively independent of estimation algorithm. Evaluation of system performance using the singular value spectrum is a generalization of STF analysis. Signal Fourier components are eigenvectors of shift-invariant systems, with eigenvalues

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