Improving the tracking capability of adaptive filters via convex combination

As is well known, Hessian-based adaptive filters (such as the recursive-least squares algorithm (RLS) for supervised adaptive filtering, or the Shalvi-Weinstein algorithm (SWA) for blind equalization) converge much faster than gradient-based algorithms [such as the least-mean-squares algorithm (LMS) or the constant-modulus algorithm (CMA)]. However, when the problem is tracking a time-variant filter, the issue is not so clear-cut: there are environments for which each family presents better performance. Given this, we propose the use of a convex combination of algorithms of different families to obtain an algorithm with superior tracking capability. We show the potential of this combination and provide a unified theoretical model for the steady-state excess mean-square error for convex combinations of gradient- and Hessian-based algorithms, assuming a random-walk model for the parameter variations. The proposed model is valid for algorithms of the same or different families, and for supervised (LMS and RLS) or blind (CMA and SWA) algorithms.

A Class of Channels Resulting in Ill-Convergence for CMA in Decision Feedback Equalizers

This paper analyzes the convergence of the constant modulus algorithm (CMA) in a decision feedback equalizer using only a feedback filter. Several works had already observed that the CMA presented a better performance than decision directed algorithm in the adaptation of the decision feedback equalizer, but theoretical analysis always showed to be difficult specially due to the analytical difficulties presented by the constant modulus criterion. In this paper, we surmount such obstacle by using a recent result concerning the CM analysis, first obtained in a linear finite impulse response context with the objective of comparing its solutions to the ones obtained through the Wiener criterion. The theoretical analysis presented here confirms the robustness of the CMA when applied to the adaptation of the decision feedback equalizer and also defines a class of channels for which the algorithm will suffer from ill-convergence when initialized at the origin.

Evaluation of plaque composition by intravascular ultrasound ""virtual histology"": the impact of dense calcium on the measurement of necrotic tissue

Aims: We aimed to evaluate if the co-localisation of calcium and necrosis in intravascular ultrasound virtual histology (IVUS-VH) is due to artefact, and whether this effect can be mathematically estimated. Methods and results: We hypothesised that, in case calcium induces an artefactual coding of necrosis, any addition in calcium content would generate an artificial increment in the necrotic tissue. Stent struts were used to simulate the ""added calcium"". The change in the amount and in the spatial localisation of necrotic tissue was evaluated before and after stenting (n=17 coronary lesions) by means of a especially developed imaging software. The area of ""calcium"" increased from a median of 0.04 mm(2) at baseline to 0.76 mm(2) after stenting (p<0.01). In parallel the median necrotic content increased from 0.19 mm(2) to 0.59 mm(2) (p<0.01). The ""added"" calcium strongly predicted a proportional increase in necrosis-coded tissue in the areas surrounding the calcium-like spots (model R(2)=0.70; p<0.001). Conclusions: Artificial addition of calcium-like elements to the atherosclerotic plaque led to an increase in necrotic tissue in virtual histology that is probably artefactual. The overestimation of necrotic tissue by calcium strictly followed a linear pattern, indicating that it may be amenable to mathematical correction.

Avoiding Divergence in the Shalvi-Weinstein Algorithm

The most popular algorithms for blind equalization are the constant-modulus algorithm (CMA) and the Shalvi-Weinstein algorithm (SWA). It is well-known that SWA presents a higher convergence rate than CMA. at the expense of higher computational complexity. If the forgetting factor is not sufficiently close to one, if the initialization is distant from the optimal solution, or if the signal-to-noise ratio is low, SWA can converge to undesirable local minima or even diverge. In this paper, we show that divergence can be caused by an inconsistency in the nonlinear estimate of the transmitted signal. or (when the algorithm is implemented in finite precision) by the loss of positiveness of the estimate of the autocorrelation matrix, or by a combination of both. In order to avoid the first cause of divergence, we propose a dual-mode SWA. In the first mode of operation. the new algorithm works as SWA; in the second mode, it rejects inconsistent estimates of the transmitted signal. Assuming the persistence of excitation condition, we present a deterministic stability analysis of the new algorithm. To avoid the second cause of divergence, we propose a dual-mode lattice SWA, which is stable even in finite-precision arithmetic, and has a computational complexity that increases linearly with the number of adjustable equalizer coefficients. The good performance of the proposed algorithms is confirmed through numerical simulations.

SKAN: Skin Scanner - System for Skin Cancer Detection Using Adaptive Techniques

SKAN: Skin Scanner - System for Skin Cancer Detection Using Adaptive Techniques - combines computer engineering concepts with areas like dermatology and oncology. Its objective is to discern images of skin cancer, specifically melanoma, from others that show only common spots or other types of skin diseases, using image recognition. This work makes use of the ABCDE visual rule, which is often used by dermatologists for melanoma identification, to define which characteristics are analyzed by the software. It then applies various algorithms and techniques, including an ellipse-fitting algorithm, to extract and measure these characteristics and decide whether the spot is a melanoma or not. The achieved results are presented with special focus on the adaptive decision-making and its effect on the diagnosis. Finally, other applications of the software and its algorithms are presented.

Effects of margarines and butter consumption on lipid profiles, inflammation markers and lipid transfer to HDL particles in free-living subjects with the metabolic syndrome

Objective: Our purpose was to examine the effects of daily servings of butter, no-trans-fat margarine and plant sterol margarine, within recommended amounts, on plasma lipids, apolipoproteins (Apos), biomarkers of inflammation and endothelial dysfunction, and on the transfer of lipids to HDL particles in free-living subjects with the metabolic syndrome. Methods: This was a randomized, single-blind study where 53 metabolic syndrome subjects (62% women, mean age 54 years) received isocaloric servings of butter, no-trans-fat margarine or plant sterol margarine in addition to their usual diets for 5 weeks. The main outcome measures were plasma lipids, Apo, inflammatory and endothelial dysfunction markers (CRP, IL-6, CD40L or E-selectin), small dense LDL cholesterol concentrations and in vitro radioactive lipid transfer from cholesterol-rich emulsions to HDL. Difference among groups was evaluated by analysis of variance. Results: There was a significant reduction in Apo-B (-10.4 %, P = 0.043) and in the Apo-B/Apo-A-1 ratio (-11.1%, P = 0.034) with plant sterol margarine. No changes in plasma lipids were noticed with butter and no-trans-fat margarine. Transfer rates of lipids to HDL were reduced in the no-trans-fat margarine group: triglycerides -42.0%, (P<0.001 vs butter and sterol margarine) and free cholesterol -16.2% (P = 0.006 vs sterol margarine). No significant effects were noted on the concentrations of inflammatory and endothelial dysfunction markers among the groups. Conclusions: In free-living subjects with the metabolic syndrome consumption of plant sterol and no-trans-fat margarines within recommended amounts reduced, respectively, Apo-B concentrations and the ability of HDL to accept lipids. European Journal of Clinical Nutrition (2010) 64, 1141-1149; doi:10.1038/ejcn.2010.122; published online 21 July 2010

Pleiotropic Effects With Equivalent Low-density Lipoprotein Cholesterol Reduction: Comparative Study Between Simvastatin and Simvastatin/Ezetimibe Coadministration

Background: Coadministration of any statin with ezetimibe is as effective as using high doses of the same statin in the reduction Of tow-density lipoprotein cholesterol (LDL-c). There may be other effects called pleiotropics. Objective: To compare the effectiveness of 2 different treatments that obtain equivalent LDL-c reductions (80 mg of simvastatin, once a clay and coadministration of 10 mg of simvastatin and 10 mg of ezetimibe, once a day) over endothelial function and inflammation. Methods: Twenty-three randomized patients with hypercholesterolemia in a 2 X 2 crossover protocol were Studied. Endothelial function was analyzed by ultrasound assessment of endothelial dependent flow-mediated vasodilation of the brachial artery, and inflammation was estimated by high-sensitivity C-reactive protein (hs-CRP). Results: LDL-c reduction was similar between the 2 treatments with simvastatin/ezetimibe and with simvastatin (P < 0.001); no difference between treatments was found (P = 0.968). Both treatments improved significantly the endothelial function [3.61% with simvastatin/ezetimibe (P = 0.003) and 5.08%. with simvastatin (P < 0.001)]; no difference was found between the 2 treatments (P = 0.291). hs-CRP had a 23% reduction with simvastatin/ezetimibe (P = 0.004) and a 30% reduction with simvastatin alone (P = 0.01), with no significant difference between the 2 treatments (P = 0.380). Conclusion: The 2 forms of treatment presented similar pleiotropic effects: improvement in endothelial function and decrease in hsCRP levels.