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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.

Thesis (M.A.)--Boston University / PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you. / This paper is divided into five sections. It is concerned with the derivation and application of a formula known as Quadrature by Differentiation. Section One derives the basic formula by applying integration by parts to a suitably chosen 2n^th. degree polynomial. By applying this method to a polynomial of degree m + n, Hummel and Seebeck's Generalized Taylor Expansion is obtained and shown identical with the Quadrature Formula when m is set equal to n. Finally the quadrature approximation is proved convergent if f(x) is analytic in a certain domain of the complex plane. Section Two deals with the representation of certain elementary functions using quadrature methods. These expansions, because they have integer coefficients and appear in a rational form, are far easier to compute than the corresponding Maclaurin Series with the same degree of accuracy. Section Three uses quadrature methods to solve ordinary differential equations whose boundary data are given at a single point. The method that is devoloped is a variation of the predictor corrector type. It is very accurate and is easily extended to solve almost every type of initial value problem. Section Four treats the linear "Two Point" and eigenvalue problem. This is accomplished by transforming the given differential equation into a system of linear algebraic relationships between the known and unknown boundary conditions. This section also deals briefly with the non linear "Two Point Problem" suggesting a iterative method, based on the results of Section Three, to obtain the missing boundary data. Section Five improves on something that Quadrature by Differentiation already is; an accurate integration formula. This is achieved by replacing derivatives with central differences. The final result is three integration formulas based only on the tabular values of the function being integrated. Since these formulas are derived using the basic interval, xg< x < xg + h, integration can be extended into s successive intervals using the same or different values of h. / 2031-01-01

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