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Clearly, the spectral components of the received signal are given by a sum of complex exponentials, where the unknown time delays tl appear as complex frequencies while propagation coef cients al appear as unknown weights Therefore, by considering the frequency domain representation of the received signal, one can convert the problem of estimating the unknown channel parameters {tl }L and l 1 {al }L into the classical harmonic retrieval problem, commonly encountered in l 1 spectral estimation [25] High-resolution harmonic retrieval is well-studied: there exists a rich body of literature on both theoretical limits and ef cient algorithms for reliable estimation [15, 16, 21, 23] There is a particularly attractive class of model-based algorithms, called super-resolution methods, which can resolve closely spaced sinusoids from a short record of noise-corrupted data.

Although this seems basic, finding a memorable name for your item can make a big difference when you go to pull the item for shipping. So, I call this one, bronze soccer boy. Please see Figure 9.3 to see what this piece looks like.

The top types of mortgage fraud include the following:37 Misrepresentation of income, assets or other debt Forged or fraudulent documents such as tax returns or rent veri cations Misrepresentation of the borrower s intent to occupy the house as his or her primary residence Identity fraud through the unauthorized use of another person s Social Security number Straw buyers (someone who is not the actual buyer) used to help family or friends obtain a house Of course, mortgage lenders and federal authorities should try to prevent these practices by borrowers and take legal actions when these practices are discovered At the same time, the United States should address three structural incentives that encourage home purchasers to overextend themselves: mortgage loans with no down payments, state exemptions from foreclosure liabilities, and unduly broad tax deductions for mortgage interest..

In [23, 25], a polynomial realization is discussed, where the parameters are estimated from zeros of the so-called prediction or annihilating lter In [23], a state space method is proposed to estimate parameters of superimposed complex exponentials in noise, which provides an elegant and numerically robust tool for parameter estimation using a subspace-based approach The ESPRIT algorithm is developed in [21], which can be viewed as a generalization of the state space method applicable to general antenna arrays In [16], several subspace techniques for estimating generalized eigenvalues of matrix pencils are addressed, such as the Direct matrix pencil algorithm, Pro-ESPRIT, and its improved version TLS-ESPRIT Another class of algorithms is based on the optimal maximum likelihood (ML) estimator [30], however, ML methods require L-dimensional search and are computationally more time-consuming than the subspace-based algorithms.

A snapshot of activity and possible distribution of the recommended robots (i.e., robot.1 to robot.6) during execution of the above-mentioned scenarios is depicted in Figure 8.8. The state-checking robots 2 and 5 are currently serving patients in beds with numbers, respectively, 6 and 2, and life support robots 3 and 4 are serving patients in beds 6 and 4 where, for example, robot.3 is called by state-checking robot.2, and robot.4 is working on a direct request from the patient. The casual positions of the cleaning robots, performing jobs within the given vicinity of randomly selected physical nodes, are shown in the picture too.

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Besides, in most cases encountered in practice, subspace methods can achieve performance close to that of the ML estimator [15], and are thus considered to be a viable alternative, provided that a low-rank system model is available In the following, we will adopt a model-based approach and show that it is possible to obtain high-resolution estimates of all the relevant parameters by sampling the received signal below the traditional Nyquist rate The general setup we will be considering is shown in Figure 21 We will rst discuss a polynomial realization of the estimator, which provides a good insight into fundamental principles behind high-resolution estimation from a subsampled version of the received signal Later, we will present a more practical, subspace-based approach 223 Polynomial Realization of the Model-Based Methods.

Jobs can be submitted directly to a cluster from an LSF host, or via Globus (GT2 or earlier versions of Globus), as shown in Figure 6.23. The Globus host is con gured with LSF jobmanager provided by Globus. When using an LSF jobmanager, jobs are submitted to the Globus resource, e.g. using globus_job_run. However, instead of forking the jobs on the local machine, jobs are re-submitted by Globus to LSF using the bsub tool.