Implementation of RNS-Based Distributed Arithmetic Discrete Wavelet Transform Architectures Using Field-Programmable Logic

Currently there are design barriers inhibiting the implementation of high-precision digital signal processing (DSP) objects with field programmable logic (FPL) devices. This paper explores overcoming these barriers by fusing together the popular distributed arithmetic (DA) method with the residue number system (RNS) for use in FPL-centric designs. The new design paradigm is studied in the context of a high-performance filter bank and a discrete wavelet transform (DWT). The proposed design paradigm is facilitated by a new RNS accumulator structure based on a carry save adder (CSA). The reported methodology also introduces a polyphase filter structure that results in a reduced look-up table (LUT) budget. The 2C-DA and RNS-DA are compared, in the context of a FPL implementation strategy, using a discrete wavelet transform (DWT) filter bank as a common design theme. The results show that the RNS-DA, compared to a traditional 2C-DA design, enjoys a performance advantage that increases with precision (wordlength).     

Light-induced electron spin polarization in the ground state of water-soluble copper porphyrins

Light-induced spin-polarized transient EPR spectra are reported for several water-soluble copper porphyrins. The spectra are assigned to the doublet ground state, with emissive spin polarization resulting from photoexcitation and subsequent electronic relaxation. In contrast to other systems for which polarization of a doublet ground state has been observed, the exchange interactions in the copper porphyrins are strong and the geometry is fixed. It is proposed that intersystem crossing from the photoexcited trip-doublet to the trip-quartet state can lead to net polarization of the spin system and that this polarization is maintained during electronic decay, possibly via charge-transfer and exciplex states. The intensity of the observed spin polarization is essentially independent of the molecular orientation in the external field, but is strongly dependent on the nature of the charged peripheral groups. Possible reasons for this behavior are discussed.     

Introduction of a nonlinearity measure for principal component models

Although principal component analysis (PCA) is an important tool in standard multivariate data analysis, little interest has been devoted to assessing whether the underlying relationship within a given variable set can be described by a linear PCA model or whether nonlinear PCA must be utilized. This paper addresses this deficiency by introducing a nonlinearity measure for principal component models. The measure is based on the following two principles: (i) the range of recorded process operation is divided into smaller regions; and (ii) accuracy bounds are determined for the sum of the discarded eigenvalues. If this sum is within the accuracy bounds for each region, the process is assumed to be linear and vice versa. This procedure is automated through the use of cross-validation. Finally, the paper shows the utility of the new nonlinearity measure using two simulation studies and with data from an industrial melter process.     

Quantitative measurement of gas hold-up distribution in a stirred chemical reactor using X-ray cone-beam computed tomography

Cone-beam type X-ray computed tomography (CBCT) is a potential method to measure three-dimensional phase distributions in vessels. An example for that is the measurement of gas profiles in stirred chemical reactors. Such data are highly valuable for the assessment and evaluation of chemical processes, for optimisation of the reactor and stirrer design, and for evaluation of computational fluid dynamics codes used to model the fluid flow and heat transfer in reactive systems. However, there are considerable difficulties for accurate quantitative measurements due to beam hardening and radiation scattering effects. In a theoretical and experimental work we have investigated the non-linear effects of both physical phenomena and developed a suitable measurement setup as well as calibration and software correction methods to achieve a highly accurate measurement of void fraction profiles with CBCT.     

Smaller superconcentrators of density 28

An N-superconcentrator is a directed, acyclic graph with N input nodes and N output nodes such that every subset of the inputs and every subset of the outputs of same cardinality can be connected by node-disjoint paths. It is known that linear-size and bounded-degree superconcentrators exist. Here it is proved that such superconcentrators exist (by a random construction of certain expander graphs as building blocks) having density 28 (where the density is the number of edges divided by N). The best known density before this paper was 34.2 [U. Schöning, Construction of expanders and superconcentrators using Kolmogorov complexity, J. Random Structures Algorithms 17 (2000) 64-77] or 33 [L.A. Bassalygo, Personal communication, 2004].     

A note on a local twist estimator

For the construction of composite surfaces interpolating a given curve net a new local twist estimator was proposed recently (Farin and Hagen, 1992). Some properties of this estimator—including an explicit representation for Gaussian curvature K at the knots of the curve net—are presented in this note.     

Improving sub-pixel accuracy for long range stereo

Dense stereo algorithms are able to estimate disparities at all pixels including untextured regions. Typically these disparities are evaluated at integer disparity steps. A subsequent sub-pixel interpolation often fails to propagate smoothness constraints on a sub-pixel level.We propose to increase the sub-pixel accuracy in low-textured regions in four possible ways: First, we present an analysis that shows the benefit of evaluating the disparity space at fractional disparities. Second, we introduce a new disparity smoothing algorithm that preserves depth discontinuities and enforces smoothness on a sub-pixel level. Third, we present a novel stereo constraint (gravitational constraint) that assumes sorted disparity values in vertical direction and guides global algorithms to reduce false matches, especially in low-textured regions. Finally, we show how image sequence analysis improves stereo accuracy without explicitly performing tracking. Our goal in this work is to obtain an accurate 3D reconstruction. Large-scale 3D reconstruction will benefit heavily from these sub-pixel refinements.Results based on semi-global matching, obtained with the above mentioned algorithmic extensions are shown for the Middlebury stereo ground truth data sets. The presented improvements, called ImproveSubPix, turn out to be one of the top-performing algorithms when evaluating the set on a sub-pixel level while being computationally efficient. Additional results are presented for urban scenes. The four improvements are independent of the underlying type of stereo algorithm.