No description available.

Future generation of wireless systems will feature high data rates and be implemented in low voltage CMOS technologies. Direct conversion receivers (DCRs) will be used in such systems which will require low voltage RF front-ends with adequate linearity. The down-converter in a DCR is a critical block in determining linearity. In addition to detailed DCR modeling in MATLAB, this thesis, completed in 2005, deals with the design and characterization of a 1V, 8GHz quadrature down-converter. It consists of two mixers and a quadrature generator implemented in a 0.18m CMOS technology. The mixer architecture proposed in this work uses a new trans-conductor. It simultaneously satisfies the low voltage and high linearity requirements. It also relaxes the inherent trade-off between gain and linearity governing CMOS active mixers. The implemented mixer occupies an area of 320 x 400 m2 and exhibits a power conversion gain of +6.5dB, a P-1dB of -5.5dBm, an IIP3 of +3.5dBm, an IIP2 of better than +48dBm, a noise figure of 11.5dB, an LO to RF isolation of 60dB at 8GHz and consumes 6.9mW of power from a 1V supply. The proposed quadrature generator circuit features a new architecture which embeds the quadrature generation scheme into the LO-buffer using active inductors. The circuit offers easy tune-ability for process, supply and temperature variations by relaxing the coupling between amplitude and phase tuning of the outputs. The implemented circuit occupies an area of 150 x 90m2 and exhibits an amplitude and quadrature phase accuracy of 1 dB and 1.5° respectively over a bandwidth of 100 MHz with a power consumption of 12mW from a 1V supply including the LO-buffer. The quadrature down-converter features an image rejection ratio of better than 40 dB and satisfies the potential target specifications of future mobile phones, extracted in this work.

Future generation of wireless systems will feature high data rates and be implemented in low voltage CMOS technologies. Direct conversion receivers (DCRs) will be used in such systems which will require low voltage RF front-ends with adequate linearity. The down-converter in a DCR is a critical block in determining linearity. In addition to detailed DCR modeling in MATLAB, this thesis, completed in 2005, deals with the design and characterization of a 1V, 8GHz quadrature down-converter. It consists of two mixers and a quadrature generator implemented in a 0.18m CMOS technology. The mixer architecture proposed in this work uses a new trans-conductor. It simultaneously satisfies the low voltage and high linearity requirements. It also relaxes the inherent trade-off between gain and linearity governing CMOS active mixers. The implemented mixer occupies an area of 320 x 400 m2 and exhibits a power conversion gain of +6.5dB, a P-1dB of -5.5dBm, an IIP3 of +3.5dBm, an IIP2 of better than +48dBm, a noise figure of 11.5dB, an LO to RF isolation of 60dB at 8GHz and consumes 6.9mW of power from a 1V supply. The proposed quadrature generator circuit features a new architecture which embeds the quadrature generation scheme into the LO-buffer using active inductors. The circuit offers easy tune-ability for process, supply and temperature variations by relaxing the coupling between amplitude and phase tuning of the outputs. The implemented circuit occupies an area of 150 x 90m2 and exhibits an amplitude and quadrature phase accuracy of 1 dB and 1.5° respectively over a bandwidth of 100 MHz with a power consumption of 12mW from a 1V supply including the LO-buffer. The quadrature down-converter features an image rejection ratio of better than 40 dB and satisfies the potential target specifications of future mobile phones, extracted in this work.

The circuit described in this study is intended for Magnetic Resonance Imaging (MRI) application. The function of this circuit is to transmit RF energy to the sample and then receive the RF energy. The circuit that does this is called a birdcage coil. This coil is capable of producing a very homogenous B1 field over a large volume; it is this aspect of birdcage coils that make them very favorable for animal/human studies as it is necessary that all nuclei in the volume of the coil are excited by uniform RF energy. At high-field (4.7T) when the power is fed to the coil at a single port the coil unable to produce a homogenous B1 field. However when power is fed at multiple ports the performance of the coil improves. In this paper a study is carried out comparing the performance of the coil when power is fed at a single port and two ports. The advantage of feeding at two ports is that there is sqrt(2) improvement in SNR and the RF power efficiency is doubled. In this work strategies are presented for matching, tuning and isolating the two ports. Also, an attempt is made to fabricate a mechanically rigid coil and interfacing the coil with some additional features that will make the coil easy to use. The homogeneity and SNR of a birdcage coil in linear and quadrature mode loaded with saline, oil and CuSO4 phantom was measured on the bench and the scanner. The coil performance was compared to two other birdcage coils in the lab. It was found that the unshielded trombone coil that was 3 times smaller in volume than the coil presented has 140% higher SNR than the coil presented but the homogenous region of the coil presented is 48% higher than the smaller coil. Lastly on the bench; the SNR of the quadrature coil was 30% higher than the coil in the linear mode.

No description available.

No description available.

The objective of this work is the development of novel, efficient and reliable multidi- mensional adaptive quadrature routines defined over simplices (MAQS). MAQS pro- vides an approximation to the integral of a function defined over the unit hypercube and provides an error estimate that is used to drive a global subdivision strategy. The quadrature estimate is based on Lagrangian interpolation defined by using the vertices, edge nodes and interior points of a given simplex. The subdivision of a given simplex is chosen to allow for the reuse of points (thus function evaluations at those points) in successive refinements of the initial tessellation. While theory is developed for smooth functions, this algorithm is well suited for functions with discontinuities in dimensions three through six. Other advantages of this approach include straight-forward parallel implementation and application to integrals over polyhedral domains. / Ph. D.

This project presents a modified method of numerical integration for a “well behaved� function over the finite interval [-1,1]. Similar to the Clenshaw-Curtis quadrature rule, this new algorithm relies on expressing the integrand as an expansion of Chebyshev polynomials of the second kind. The truncated series is integrated term-by-term yielding an approximation for the integral of which we wish to compute. The modified method is then contrasted with its predecessor Clenshaw-Curtis, as well as the classical method of Gauss-Legendre in terms of convergence behavior, error analysis and computational efficiency. Lastly, illustrative examples are shown which demonstrate the dependence that the convergence has on the given function to be integrated.

This thesis advocates the use of maximum likelihood analysis for generalized regression models with measurement error in a single explanatory variable. This will be done first by presenting a computational algorithm and the numerical details for carrying out this algorithm on a wide variety of models. The computational methods will be based on the EM algorithm in conjunction with the use of Gauss-Hermite quadrature to approximate integrals in the E-step. Second, this thesis will demonstrate the relative superiority of likelihood-ratio tests and confidence intervals over those based on asymptotic normality of estimates and standard errors, and that likelihood methods may be more robust in these situations than previously thought. The ability to carry out likelihood analysis under a wide range of distributional assumptions, along with the advantages of likelihood ratio inference and the encouraging robustness results make likelihood analysis a practical option worth considering in regression problems with explanatory variable measurement error. / Graduation date: 1999

In this dissertation, we discuss an adaptive angular discretization scheme for the neutral-particle transport equation in three dimensions. We mesh the direction domain by dividing the faces of a regular octahedron into equilateral triangles and projecting these onto “spherical triangles” on the surface of the sphere. We choose four quadrature points per triangle, and we define interpolating basis functions that are linear in the direction cosines. The quadrature point’s weight is the integral of the point’s linear discontinuous finite element (LDFE) basis function over its local triangle. Variations in the locations of the four points produce variations in the quadrature set. The new quadrature sets are amenable to local refinement and coarsening, and hence can be used with an adaptive algorithm. If local refinement is requested, we use the LDFE basis functions to build an approximate angular flux, interpolated, by interpolation through the existing four points on a given triangle. We use a transport sweep to find the actual values, calc, at certain test directions in the triangle and compare against interpolated at those directions. If the results are not within a userdefined tolerance, the test directions are added to the quadrature set. The performance of our uniform sets (no local refinement) is dramatically better than that of commonly used sets (level-symmetric (LS), Gauss-Chebyshev (GC) and variants) and comparable to that of the Abu-Shumays Quadruple Range (QR) sets. On simple problems, the QR sets and the new sets exhibit 4th-order convergence in the scalar flux as the directional mesh is refined, whereas the LS and GC sets exhibit 1.5-order and 2nd-order convergence, respectively. On difficult problems (near discontinuities in the direction domain along directions that are not perpendicular to coordinate axes), these convergence orders diminish and the new sets outperform the others. We remark that the new LDFE sets have strictly positive weights and that arbitrarily refined sets can be generated without the numerical difficulties that plague the generation of high-order QR sets. Adapted LDFE sets are more efficient than uniform LDFE sets only in difficult problems. This is due partly to the high accuracy of the uniform sets, partly to basing refinement decisions on purely local information, and partly to the difficulty of mapping among differently refined sets. These results are promising and suggest interesting future work that could lead to more accurate solutions, lower memory requirements, and faster solutions for many transport problems.